Project: Custom Website Chatbot

 

The "Project: Custom Website Chatbot" course one is designed to guide learners through the process of developing an intelligent chatbot tailored for website integration. This project focuses on creating a chatbot that can engage users effectively, providing personalized interactions and enhancing the overall user experience.

Course Overview

In this project, participants will learn to build a custom website chatbot using open-source large language models (LLMs) such as GPT-Neo or GPT-J. The chatbot will be designed to generate context-aware, human-like responses, making it suitable for various applications, including business and educational purposes. 

Key Learning Outcomes

Understanding Large Language Models (LLMs): Gain insights into the architecture and functioning of open-source LLMs like GPT-Neo and GPT-J.

Chatbot Design and Development: Learn the principles of designing conversational agents and implementing them using LLMs.

Website Integration: Acquire skills to seamlessly integrate the chatbot into a website, ensuring smooth user interactions.

Customization for Specific Needs: Tailor the chatbot's responses and behavior to meet specific business or educational requirements.

Course Structure

The curriculum is structured to provide a comprehensive learning experience:

Introduction to Chatbots and LLMs: An overview of chatbots, their applications, and the role of large language models in enhancing conversational capabilities.

Setting Up the Development Environment: Guidance on configuring the necessary tools and frameworks for chatbot development.

Implementing the Chatbot Logic: Step-by-step instructions on building the chatbot's conversational logic using GPT-Neo or GPT-J.

Integrating the Chatbot into a Website: Techniques for embedding the chatbot into a website, ensuring a user-friendly interface.

Testing and Optimization: Methods to test the chatbot's performance and optimize its responses for better user engagement.

Customization and Deployment: Strategies to customize the chatbot for specific use cases and deploy it in a live environment.

Why Enroll in This Course?

Hands-On Experience: Engage in a practical project that culminates in a functional chatbot ready for deployment.

Expert Guidance: Learn from experienced instructors with expertise in AI and chatbot development.

Comprehensive Resources: Access a wealth of materials, including tutorials, code samples, and best practices.

Career Advancement: Develop skills that are in high demand across industries focused on enhancing user engagement through intelligent interfaces.

What you will learn

• Learn to build and deploy custom chatbots on websites.
• Gain experience in designing effective conversation flows.
• Master NLP models for domain-specific responses.
• Develop skills in integrating chatbots with web frameworks.

Join Free : Project: Custom Website Chatbot

Conclusion

The "Project: Custom Website Chatbot" course by euron.one offers a valuable opportunity for individuals interested in AI and web development to create a sophisticated chatbot tailored to specific needs. By leveraging open-source LLMs, participants will be equipped to enhance user interactions on websites, providing personalized and context-aware responses.

Read More

Machine Learning Project : Production Grade Deployment

 

Deploying a machine learning model is more than just training a model and making predictions. It involves making the model scalable, reliable, and efficient in real-world environments. The "Machine Learning Project: Production Grade Deployment" course is designed to equip professionals with the necessary skills to take ML models from research to production. This blog explores the key concepts covered in the course and why production-grade deployment is crucial.

Importance of Production-Grade Machine Learning Deployment

In a real-world scenario, deploying an ML model means integrating it with business applications, handling real-time requests, and ensuring it remains accurate over time. A model that works well in a Jupyter Notebook may not necessarily perform efficiently in production. Challenges such as model drift, data pipeline failures, and scalability issues need to be addressed.

This course provides a structured approach to making ML models production-ready by covering essential concepts such as:

Model Packaging & Versioning

API Development for Model Serving

Containerization with Docker & Kubernetes

Cloud Deployment & CI/CD Pipelines

Monitoring & Model Retraining

Key Components of the Course

1. Model Packaging & Versioning

Once an ML model is trained, it needs to be saved and prepared for deployment. The course covers:

• How to save and serialize models using Pickle, Joblib, or ONNX.
• Versioning models to track improvements using tools like MLflow and DVC.
• Ensuring reproducibility by logging dependencies and environment configurations.

2. API Development for Model Serving

An ML model needs an interface to interact with applications. The course teaches:

• How to develop RESTful APIs using Flask or FastAPI to serve model predictions.
• Creating scalable endpoints to handle multiple concurrent requests.
• Optimizing response times for real-time inference.

3. Containerization with Docker & Kubernetes

To ensure consistency across different environments, containerization is a key aspect of deployment. The course includes:

• Creating Docker containers for ML models.
• Writing Dockerfiles and managing dependencies.
• Deploying containers on Kubernetes clusters for scalability.
• Using Helm Charts for Kubernetes-based ML deployments.

4. Cloud Deployment & CI/CD Pipelines

Deploying ML models on the cloud enables accessibility and scalability. The course covers:

• Deploying models on AWS, Google Cloud, and Azure.
• Setting up CI/CD pipelines using GitHub Actions, Jenkins, or GitLab CI/CD.
• Automating model deployment with serverless options like AWS Lambda.

5. Monitoring & Model Retraining

Once a model is in production, continuous monitoring is crucial to maintain performance. The course introduces:

• Implementing logging and monitoring tools like Prometheus and Grafana.
• Detecting model drift and setting up alerts.
• Automating retraining pipelines with feature stores and data engineering tools.

Overcoming Challenges in ML Deployment

Scalability Issues: Ensuring models can handle high traffic loads.

Model Drift: Addressing changes in data patterns over time.

Latency Optimization: Reducing response times for real-time applications.

Security Concerns: Preventing unauthorized access and ensuring data privacy.

What you will learn

• Understand the full ML deployment lifecycle.
• Package and prepare machine learning models for production.
• Develop APIs to serve models using Flask or FastAPI.
• Containerize models using Docker for easy deployment.
• Deploy models on cloud platforms like AWS, GCP, or Azure.
• Ensure model scalability and performance in production.
• Implement monitoring and logging for deployed models.
• Optimize models for efficient production environments.

Join Free : Machine Learning Project : Production Grade Deployment

Conclusion:

The "Machine Learning Project: Production Grade Deployment" course by Euron is ideal for data scientists, ML engineers, and software developers who want to bridge the gap between ML models and real-world applications. By mastering these concepts, learners can build robust, scalable, and high-performing ML systems that are ready for production use.

Read More

Python Coding Challange - Question With Answer(01030225)

 

Code:

my_list = [3, 1, 10, 5]
my_list = my_list.sort()
print(my_list)

---

Step 1: Creating the list

my_list = [3, 1, 10, 5]

• A list named my_list is created with four elements: [3, 1, 10, 5].

---

Step 2: Sorting the list

my_list = my_list.sort()

• The .sort() method is called on my_list.

• The .sort() method sorts the list in place, which means it modifies the original list directly.

• However, .sort() does not return anything. Its return value is None.

  As a result, when you assign the result of my_list.sort() back to my_list, the variable my_list now holds None.

---

Step 3: Printing the list

print(my_list)

• Since my_list is now None (from the previous step), the output of this code will be:

  
  None

---

Correct Way to Sort and Print:

If you want to sort the list and keep the sorted result, you should do the following:

1. Sort in place without reassignment:

   
   my_list = [3, 1, 10, 5]
   my_list.sort() # This modifies the original list in place
   print(my_list) # Output: [1, 3, 5, 10]

2. Use the sorted() function:

   
   my_list = [3, 1, 10, 5]
   my_list = sorted(my_list) # sorted() returns a new sorted list 
   print(my_list) # Output: [1, 3, 5, 10]
   
   

Key Difference Between sort() and sorted():

• sort(): Modifies the list in place and returns None.
• sorted(): Returns a new sorted list and does not modify the original list.

In your original code, the mistake was trying to assign the result of sort() to my_list. Use one of the correct methods shown above depending on your requirements.

Read More

18 Insanely Useful Python Automation Scripts I Use Everyday

 Here’s a list of 18 insanely useful Python automation scripts you can use daily to simplify tasks, improve productivity, and streamline your workflow:

---

1. Bulk File Renamer

Rename files in a folder based on a specific pattern.

import os
for i, file in enumerate(os.listdir("your_folder")): 
    os.rename(file, f"file_{i}.txt")

---

2. Email Sender

Send automated emails with attachments.

import smtplib  
from email.mime.text import MIMEText 
from email.mime.multipart import MIMEMultipart 

msg = MIMEMultipart() 
msg['From'] = "you@example.com" 
msg['To'] = "receiver@example.com" 
msg['Subject'] = "Subject" 
msg.attach(MIMEText("Message body", 'plain')) 

server = smtplib.SMTP('smtp.gmail.com', 587)
server.starttls() server.login("you@example.com", "password") 
server.sendmail(msg['From'], msg['To'], msg.as_string())
server.quit()

---

3. Web Scraper

Extract useful data from websites.

import requests  
from bs4 import BeautifulSoup 
url = "https://example.com" 
soup = BeautifulSoup(requests.get(url).text, 'html.parser') 
print(soup.title.string)

---

4. Weather Notifier

Fetch daily weather updates.

import requests  
city = "London" 
url = f"https://wttr.in/{city}?format=3" 
print(requests.get(url).text)

---

5. Wi-Fi QR Code Generator

Generate QR codes for your Wi-Fi network.

from wifi_qrcode_generator import wifi_qrcode  
wifi_qrcode("YourSSID", False, "WPA", "YourPassword").show()

---

6. YouTube Video Downloader

Download YouTube videos in seconds.

from pytube import YouTube  
YouTube("video_url").streams.first().download()

---

7. Image Resizer

Resize multiple images at once.

from PIL import Image  
Image.open("input.jpg").resize((500, 500)).save("output.jpg")

---

8. PDF Merger

Combine multiple PDFs into one.

from PyPDF2 import PdfMerger  
merger = PdfMerger() 
for pdf in ["file1.pdf", "file2.pdf"]: 
    merger.append(pdf) 
merger.write("merged.pdf")

---

9. Expense Tracker

Log daily expenses in a CSV file.

import csv  
with open("expenses.csv", "a") as file: 
     writer = csv.writer(file)  
     writer.writerow(["Date", "Description", "Amount"])

---

10. Automated Screenshot Taker

Capture screenshots programmatically.

import pyautogui  
pyautogui.screenshot("screenshot.png")

---

11. Folder Organizer

Sort files into folders by type.

import os, shutil  
for file in os.listdir("folder_path"): 
    ext = file.split('.')[-1] 
    os.makedirs(ext, exist_ok=True)  
    shutil.move(file, ext)

---

12. System Resource Monitor

Check CPU and memory usage.

import psutil  
print(f"CPU: {psutil.cpu_percent()}%, Memory: {psutil.virtual_memory().percent}%")

---

13. Task Scheduler

Automate repetitive tasks with schedule.

import schedule, time  
schedule.every().day.at("10:00").do(lambda: print("Task executed")) 
while True:  
    schedule.run_pending()     
    time.sleep(1)

---

14. Network Speed Test

Measure internet speed.

from pyspeedtest import SpeedTest  
st = SpeedTest() 
print(f"Ping: {st.ping()}, Download: {st.download()}")

---

15. Text-to-Speech Converter

Turn text into audio.

import pyttsx3  
engine = pyttsx3.init() 
engine.say("Hello, world!") 
engine.runAndWait()

---

16. Password Generator

Create secure passwords.

import random, string  
print(''.join(random.choices(string.ascii_letters + string.digits, k=12)))

---

17. Currency Converter

Convert currencies with real-time rates.

import requests  
url = "https://api.exchangerate-api.com/v4/latest/USD" 
rates = requests.get(url).json()["rates"] 
print(f"USD to INR: {rates['INR']}")

---

18. Automated Reminder

Pop up reminders at specific times.

from plyer import notification  
notification.notify(title="Reminder", message="Take a break!", timeout=10)

Read More

Python Coding Challange - Question With Answer(01310125)

 

Explanation:

1. Assignment (x = 7, 8, 9):

   • Here, x is assigned a tuple (7, 8, 9) because multiple values separated by commas are automatically grouped into a tuple in Python.
   • So, x = (7, 8, 9).

2. Printing (print(x == 7, 8, 9)):

   • The print function evaluates the arguments inside and then displays them.
   • The expression x == 7 checks if x is equal to 7. Since x is a tuple (7, 8, 9), this condition evaluates to False.
   • The other values 8 and 9 are treated as separate arguments to print.

3. Output:

   • The result of x == 7 is False.
   • The values 8 and 9 are displayed as-is.
   • Therefore, the output is:

     False 8 9

Key Concepts:

• In Python, tuples are created using commas (e.g., x = 1, 2, 3 is the same as x = (1, 2, 3)).
• When printing multiple values, the print function separates them with spaces by default.

Read More

Python Coding challenge - Day 361| What is the output of the following Python Code?

 

Code Explanation:

import matplotlib.pyplot as plt

This imports the pyplot module from the matplotlib library and gives it the alias plt.

matplotlib.pyplot is a module used for creating plots and visualizations in Python.

plt.scatter([1, 2], [3, 4])

The scatter() function creates a scatter plot where each point is plotted individually based on the given coordinates.

The function takes two lists:

First list [1, 2] represents the x-coordinates.

Second list [3, 4] represents the y-coordinates.

This results in two points:

Point 1: (1, 3)

Point 2: (2, 4)

plt.show()

This displays the plot in a window or inline (depending on the environment).

It ensures that the scatter plot is rendered and shown to the user.

Final Answer:

A: Scatter plot

Read More

Python Coding challenge - Day 360| What is the output of the following Python Code?

 

Code Explanation:

from collections import defaultdict

This imports defaultdict from Python’s collections module.

defaultdict is a specialized dictionary that provides default values for non-existent keys instead of raising a KeyError.

d = defaultdict(int)

Creates a defaultdict where the default value for missing keys is determined by int().

int() returns 0, so any key that doesn't exist will automatically have a default value of 0.

d["a"] += 1

Since "a" is not yet in d, defaultdict automatically initializes it with int(), which is 0.

Then, += 1 increments its value from 0 to 1.

print(d["a"])

Prints the value of "a", which is now 1.

Final Output:

1

Read More

Python Coding challenge - Day 359| What is the output of the following Python Code?

 

Code Explanation:

import json

This imports the json module, which provides functions to work with JSON (JavaScript Object Notation) data.

The json module allows encoding (serialization) and decoding (deserialization) of JSON data in Python.

data = {"a": 1}

This defines a Python dictionary data with a single key-value pair:

{"a": 1}

The key is "a" (a string).

The value is 1 (an integer).

print(json.dumps(data))

json.dumps(data):

The dumps() function converts a Python dictionary into a JSON-formatted string.

In JSON, the same dictionary would look like:

{"a": 1}

The dumps() function serializes the Python dictionary into a JSON string.

print(json.dumps(data)):

This prints the JSON-formatted string:

{"a": 1}

The output is a string, not a dictionary.

Final Output:

A. JSON string

Read More

Python Coding challenge - Day 358| What is the output of the following Python Code?

 

Code Explanation:

import itertools

This imports the itertools module, which provides efficient iterator functions for looping and data manipulation.

a = [1, 2]

This defines a list a with two elements: 1 and 2.

b = [3, 4]

This defines another list b with two elements: 3 and 4.

result = list(itertools.chain(a, b))

itertools.chain(a, b):

The chain() function takes multiple iterables (lists a and b in this case) and creates an iterator that produces elements from each iterable one by one.

It avoids creating a new list immediately, making it memory efficient.

list(itertools.chain(a, b)):

The chain object returned is converted into a list using list(), which collects all elements from the chained iterator into a single list.

Internally, itertools.chain(a, b) works as follows:

Takes the first iterable (a) and yields elements 1 and 2.

Moves to the next iterable (b) and yields elements 3 and 4.

The final result stored in result is:

[1, 2, 3, 4]

print(result)

This prints the final concatenated list:

[1, 2, 3, 4]

Final Output:

[1, 2, 3, 4]

Read More

Python Coding challenge - Day 357| What is the output of the following Python Code?

 

Code Explanation:

Step 1: Importing the random Module

import random

The random module in Python provides functions for generating random numbers and performing random operations.

Step 2: Creating a List

data = [1, 2, 3]

A list named data is created containing the elements [1, 2, 3].

Step 3: Shuffling the List

random.shuffle(data)

The random.shuffle() function randomly rearranges the elements of the list data in place.

Since shuffling is random, the order of elements will change each time the program runs.

Step 4: Printing the Shuffled List

print(data)

This prints the shuffled version of data after random.shuffle() is applied.

Final Answer:

A: Shuffled list

Read More

Python Coding challenge - Day 356| What is the output of the following Python Code?

 

Step 1: Importing the Pandas Library

import pandas as pd  

This line imports the pandas library, which is used for data manipulation and analysis in Python.

Step 2: Creating a Dictionary

data = {"A": [1, 2, 3]}  

A dictionary named data is created with a single key "A" and a list of values [1, 2, 3].

Step 3: Creating a DataFrame

df = pd.DataFrame(data)  

This converts the dictionary data into a pandas DataFrame.

The resulting DataFrame looks like this:

   A

0  1

1  2

2  3

Step 4: Filtering the DataFrame

df[df["A"] > 1]

Here, df["A"] > 1 creates a Boolean condition:

0    False

1     True

2     True

Name: A, dtype: bool

This condition is applied to df, keeping only the rows where column "A" has values greater than 1.

The resulting DataFrame is:

   A

1  2

2  3

Step 5: Printing the Filtered DataFrame

print(df[df["A"] > 1])

This prints the filtered output:

   A

1  2

2  3

Final Answer:

A: Rows with A > 1

Read More

Python Coding challenge - Day 355| What is the output of the following Python Code?

 

Code Explanation:

import itertools  

Imports the itertools module, which provides functions for efficient looping and combinatorial operations like permutations, combinations, and product.

data = [1, 2]  

Defines a list data containing two elements: [1, 2].

result = list(itertools.permutations(data))  

itertools.permutations(data) generates all possible ordered arrangements (permutations) of elements in data.

Since data has two elements, the possible permutations are:

(1, 2)

(2, 1)

list() converts the result into a list of tuples.

print(result)

Prints the list of permutations.

Output

[(1, 2), (2, 1)]

Read More

5 Python Tricks Everyone Must Know in 2025

 

5 Python Tricks Everyone Must Know in 2025

Python remains one of the most versatile and popular programming languages in 2025. Here are five essential Python tricks that can improve your code's efficiency, readability, and power. Let’s dive into each with a brief explanation!

---

1. Walrus Operator (:=)

The walrus operator allows assignment and evaluation in a single expression, simplifying code in scenarios like loops and conditionals.

Example:

data = [1, 2, 3, 4]
if (n := len(data)) > 3: 
   print(f"List has {n} items.") # Outputs: List has 4 items.

Why use it? It reduces redundancy by combining the assignment and the conditional logic, making your code cleaner and more concise.

---

2. F-Strings for Formatting

F-strings provide an easy and readable way to embed variables and expressions directly into strings. They're faster and more efficient than older formatting methods.

Example:

name, age = "John", 25
print(f"Hello, my name is {name} and I am {age} years old.") # Outputs: Hello, my name is John and I am 25 years old.

Why use it? F-strings improve readability, reduce errors, and allow inline expressions like {age + 1} for dynamic calculations.

---

3. Unpacking with the Asterisk (*)

Python's unpacking operator * allows you to unpack elements from lists, tuples, or even dictionaries. It's handy for dynamic and flexible coding.

Example:

numbers = [1, 2, 3, 4, 5]
first, *middle, last = numbers
print(first, middle, last) # Outputs: 1 [2, 3, 4] 5

Why use it? It’s useful for splitting or reorganizing data without manually slicing or indexing.

---

4. Using zip() to Combine Iterables

The zip() function pairs elements from multiple iterables, creating a powerful and intuitive way to process data in parallel.

Example:

names = ["Alice", "Bob", "Charlie"]
scores = [85, 90, 95]
for name, score in zip(names, scores): 
    print(f"{name}: {score}")

Why use it? zip() saves time when dealing with parallel data structures, eliminating the need for manual indexing.

---

5. List Comprehensions for One-Liners

List comprehensions are a Pythonic way to generate or filter lists in a single line. They are concise, readable, and often faster than loops.

Example:

squares = [x**2 for x in range(10) if x % 2 == 0]
print(squares) # Outputs: [0, 4, 16, 36, 64]

Why use it? List comprehensions are efficient for processing collections and reduce the need for multi-line loops.

---

Conclusion:
These five Python tricks can help you write smarter, cleaner, and faster code in 2025. Mastering them will not only improve your productivity but also make your code more Pythonic and elegant. Which one is your favorite?

Read More

Python Coding Challange - Question With Answer(01300125)

 

Code Analysis:

class Number:
    integers = [5, 6, 7]
    for i in integers:
        i * 2
print(Number.i)

1. Defining the Number class:

   • The Number class is created, and a class-level attribute integers is defined as a list: [5, 6, 7].

2. for loop inside the class body:

   • Inside the class body, a for loop iterates over each element in the integers list.
   • For each element i, the expression i * 2 is executed. However:
     • This operation (i * 2) does not store or assign the result anywhere.
     • It simply calculates the value but does not affect the class or create new attributes.
   • The variable i exists only within the scope of the for loop and is not stored as a class attribute.
3. print(Number.i):
   • After the class definition, the code attempts to access Number.i.
   • Since the variable i was used only in the loop and was never defined as an attribute of the Number class, this will raise an AttributeError:

     python
     AttributeError: type object 'Number' has no attribute 'i'

---

Key Points:

• Variables in a for loop inside a class body are temporary and are not automatically added as class attributes.
• To make i an attribute of the class, you must explicitly assign it, like so:

  
  class Number:
      integers = [5, 6, 7]
      for i in integers:
          result = i * 2 # This only calculates the value
          last_value = i # Assigns the last value to a class attribute
  
  print(Number.last_value) # Outputs: 7
  

  Here, last_value would be accessible as an attribute of the class.

Read More

Python Brasil 2025: The Heartbeat of Python in South America

 

Calling all Python enthusiasts! Python Brasil 2025 is set to be the largest gathering of Python developers, educators, and enthusiasts in South America. Known for its vibrant community and warm hospitality, Brazil offers the perfect setting for this celebration of Python and innovation.

Event Details

• Dates: October 21–27, 2025

• Location: São Paulo, Brazil

• Theme: "Python for Everyone"

• Format: In-person with virtual participation options

Why Attend Python Brasil 2025?

Python Brasil is more than just a conference; it’s a movement that brings together a diverse and inclusive community. Here’s what you can look forward to:

1. Inspiring Keynotes

Hear from global and regional Python leaders as they discuss how Python is driving innovation in areas like data science, machine learning, web development, and more.

2. Informative Talks

Enjoy a wide array of sessions tailored for everyone from beginners to advanced developers. Topics include Python libraries, frameworks, community building, and best practices.

3. Practical Workshops

Enhance your Python skills with hands-on workshops that delve into everything from Django to data visualization and automation.

4. Networking Opportunities

Meet fellow Pythonistas from Brazil and beyond, exchange ideas, and build lasting professional connections.

5. Lightning Talks

Engage in rapid-fire presentations that showcase innovative projects and ideas from the community.

6. Sprints and Hackathons

Collaborate on open-source projects and work on Python-based solutions to real-world challenges.

Who Should Attend?

Python Brasil 2025 welcomes:

• Developers eager to expand their knowledge and skills.

• Educators passionate about teaching Python.

• Students and Beginners starting their Python journey.

• Tech Entrepreneurs looking for Python-powered solutions.

Registration and Tickets

Visit the official Python Brasil 2025 website ([https://www.python.org/events/]) for ticket information and registration. Early bird tickets are available, so secure your spot today!

Be a Part of Python Brasil

Contribute to the success of Python Brasil 2025 by:

• Submitting a Talk Proposal: Share your expertise with the community.

• Volunteering: Help ensure the event runs smoothly.

• Sponsoring the Event: Highlight your organization’s support for the Python community.

Experience the Culture of Brazil

In addition to the conference, take the opportunity to explore Brazil’s rich culture, breathtaking landscapes, and world-famous cuisine. From lively cityscapes to serene beaches, Brazil has something for everyone.

Register : Python Brasil 2025

For live updates join : https://chat.whatsapp.com/JXqO91UlVJr6BKRZpTo4XG

Don’t Miss Out

Python Brasil 2025 is more than a conference—it’s a celebration of the Python community’s impact in Brazil and worldwide. Whether attending in person or virtually, you’ll leave inspired and connected.

Register now and join us in making Python Brasil 2025 an unforgettable experience. See you there!

Read More

PyCon Estonia 2025: A Python-Powered Gathering in the Digital Hub of Europe

 

Attention Pythonistas! PyCon Estonia 2025 is on its way, set to unite developers, educators, and tech enthusiasts in the heart of one of Europe’s most innovative digital nations. Known for its tech-forward culture, Estonia offers the perfect backdrop for this exciting celebration of Python.

Event Details

• Dates: October 2–3, 2025

• Location: Tallinn, Estonia

• Theme: "Coding the Future"

• Format: In-person with virtual attendance options

What Awaits You at PyCon Estonia 2025

PyCon Estonia promises a vibrant mix of technical sessions, hands-on workshops, and community events. Here’s what you can expect:

1. World-Class Keynotes

Be inspired by influential leaders from the Python community and beyond as they explore Python’s role in shaping the digital landscape.

2. Engaging Talks

Discover the latest Python advancements through a diverse range of talks. Topics will span AI, cybersecurity, web development, and Python’s role in the startup ecosystem.

3. Interactive Workshops

Roll up your sleeves and dive into workshops designed to build skills in Python programming, data analysis, and emerging technologies.

4. Community Connections

Network with Python enthusiasts from across the globe. Share ideas, collaborate on projects, and expand your professional network.

5. Lightning Talks and Panels

Enjoy fast-paced, thought-provoking presentations and interactive panel discussions that showcase the versatility of Python.

6. Open-Source Sprints

Join forces with fellow developers to contribute to open-source projects, giving back to the Python ecosystem.

Why Attend?

Whether you’re a seasoned developer, an educator, or someone new to Python, PyCon Estonia offers something for everyone:

• Developers: Stay updated on Python trends and tools.

• Entrepreneurs: Learn how Python powers innovation in startups.

• Educators: Gain insights into Python’s applications in teaching.

• Students: Kickstart your Python journey in a supportive community.

Registration and Tickets

Secure your spot today by visiting the official PyCon Estonia 2025 website ([https://www.python.org/events/]). Early bird tickets are available, so don’t delay!

Contribute to PyCon Estonia

Make PyCon Estonia 2025 even more special by:

• Submitting a Proposal: Share your knowledge by delivering a talk or workshop.

• Volunteering: Be part of the team that makes it all happen.

• Sponsoring: Showcase your brand to a tech-savvy audience.

Discover Estonia

PyCon Estonia is not just about Python—it’s an opportunity to explore one of Europe’s most digitally advanced countries. Take some time to experience Estonia’s beautiful landscapes, historic architecture, and vibrant culture.

Register : PyCon Estonia 2025

For live updates join : https://chat.whatsapp.com/Bv8qampDyKJ0nzlR5RlzjW

Join Us at PyCon Estonia 2025

PyCon Estonia 2025 is more than a conference; it’s a celebration of Python and the vibrant community that surrounds it. Don’t miss this opportunity to learn, connect, and grow.

Register now and become a part of this remarkable event. See you in Estonia!

Read More

PyCon JP 2025: Embracing Python Innovation in Japan

 

Get ready, Python enthusiasts! PyCon JP 2025 is gearing up to bring together the brightest minds in the Python community in Japan. With its focus on innovation, collaboration, and cultural exchange, PyCon JP is the ultimate destination for Python developers, educators, and enthusiasts.

Event Details

• Dates: September 26–27, 2025

• Location: Hiroshima, Japan

• Theme: "Python for a Connected World"

• Format: Hybrid (In-person and virtual attendance options)

Why Attend PyCon JP 2025?

PyCon JP is known for its engaging content and vibrant community spirit. Here’s what to expect:

1. Inspiring Keynotes

Hear from leading figures in the global Python community as they share insights on Python’s impact across industries and its role in shaping the future of technology.

2. Diverse Talks

From beginner-friendly tutorials to advanced technical sessions, the talks at PyCon JP will cover a wide range of topics, including AI, web development, data science, and more.

3. Practical Workshops

Learn by doing! Hands-on workshops will help attendees deepen their understanding of Python frameworks, tools, and libraries.

4. Community Networking

Meet Python developers from around the world, exchange ideas, and build connections that extend beyond the conference.

5. Lightning Talks

Quick, insightful presentations that spark ideas and showcase the creativity within the Python community.

6. Developer Sprints

Collaborate with fellow developers to contribute to open-source projects and give back to the Python ecosystem.

Who Should Attend?

• Developers eager to stay updated on Python trends.

• Educators looking for new ways to teach programming.

• Students and Beginners keen to start their Python journey.

• Business Leaders exploring Python’s applications in industry.

Registration and Tickets

Visit the official PyCon JP 2025 website ([https://www.python.org/events/]) for ticket information and registration details. Early bird discounts are available, so act fast!

Be a Part of PyCon JP

PyCon JP thrives on community participation. Here’s how you can get involved:

• Submit a Proposal: Present your ideas by giving a talk or running a workshop.

• Volunteer: Help make the event an unforgettable experience.

• Sponsor the Event: Highlight your company’s role in the Python ecosystem.

Experience Japan’s Culture

Beyond the conference, PyCon JP 2025 offers a chance to explore Japan’s unique culture. Enjoy traditional cuisine, visit historic landmarks, and immerse yourself in the vibrant atmosphere of the host city.

Register : PyCon JP 2025

For live updates join : https://chat.whatsapp.com/C0kgrc7sypm8yu1YjpZ5zW

Don’t Miss Out

PyCon JP 2025 is more than a conference; it’s a celebration of Python and its community. Whether you’re attending in person or virtually, you’ll leave with new knowledge, connections, and inspiration.

Register today and join us in making PyCon JP 2025 an unforgettable experience. See you there!

Read More

 

PyCon UK 2025: Building Bridges in the Python Community

Python enthusiasts, mark your calendars! PyCon UK 2025 is set to take place, bringing together developers, educators, and Python lovers from across the United Kingdom and beyond. With its rich lineup of talks, workshops, and community events, PyCon UK is more than a conference—it's a celebration of the Python ecosystem and the people who make it thrive.

Event Details

• Dates: September 19–22, 2025

• Location: Manchester, United Kingdom

• Theme: "Innovate, Educate, Collaborate"

• Format: In-person and virtual attendance options

What to Expect at PyCon UK 2025

PyCon UK has built a reputation for being a welcoming, inclusive, and inspiring event. Here’s what you can look forward to this year:

1. Keynote Speakers

Gain insights from leading voices in the Python community and beyond. Keynote speakers will cover diverse topics, from Python’s role in AI and web development to its applications in education and research.

2. Informative Talks

A wide range of sessions will cater to all levels, from beginner tutorials to advanced technical deep dives. Expect discussions on Python’s latest features, best practices, and real-world applications.

3. Interactive Workshops

Get hands-on experience with Python frameworks, libraries, and tools. Workshops are designed to help attendees sharpen their skills in areas like data science, machine learning, and software development.

4. Networking and Community Building

Meet fellow Pythonistas, share experiences, and build lasting connections during social events, coffee breaks, and community meetups.

5. Education Track

Special sessions dedicated to Python in education will showcase how the language is being used to empower learners of all ages.

6. Developer Sprints

Contribute to open-source projects and collaborate with others in the Python community during the popular sprint sessions.

Who Should Attend?

• Developers: Learn new skills and discover tools to enhance your work.

• Educators: Explore how Python can be used to teach programming effectively.

• Students and Beginners: Start your Python journey in a friendly and supportive environment.

• Community Leaders: Share ideas and gain insights into building inclusive tech communities.

Registration and Tickets

Visit the official PyCon UK 2025 website ([https://www.python.org/events/]) to register. Early bird tickets are available, so don’t miss out!

Get Involved

PyCon UK is a community-driven event, and there are plenty of ways to contribute:

• Submit a Talk or Workshop Proposal: Share your knowledge and experience.

• Volunteer: Help make the event a success.

• Sponsor the Conference: Showcase your organization’s commitment to Python and its community.

Explore the UK While You’re Here

PyCon UK isn’t just about Python—it’s also an opportunity to experience the history and culture of the UK. Take time to explore the host city, its landmarks, and its culinary delights.

Register : PyCon UK 2025

For live updates join : https://chat.whatsapp.com/DnUHvLFgFYBEv0sdMZzs2m

Join Us at PyCon UK 2025

Whether you're a seasoned developer, an educator, or someone just beginning their Python journey, PyCon UK 2025 has something for you. This conference is more than an event; it's a chance to learn, connect, and contribute to the vibrant Python community.

Don’t miss out on this exciting opportunity. Register today, and we’ll see you at PyCon UK 2025!

Read More

PyCon Italia 2025: Celebrating Python in the Heart of Italy

 

ython enthusiasts, developers, and community leaders, rejoice! PyCon Italia 2025 is set to unite the Python community in one of Europe’s most vibrant cultural hubs. From its exciting sessions to its unforgettable networking opportunities, PyCon Italia promises to deliver an enriching experience for attendees of all backgrounds and skill levels.

Event Details

• Dates: May 28–31, 2025

• Location: Bologna, Italy

• Theme: "Coding the Future Together"

• Hybrid Format: On-site and online options available

What Makes PyCon Italia Special?

PyCon Italia is not just a tech event; it’s an opportunity to immerse yourself in the Python ecosystem while embracing the charm of Italy. The conference blends high-quality Python-focused content with a sense of community and inclusivity, making it the perfect event for developers, educators, data scientists, and tech enthusiasts.

Key Highlights of PyCon Italia 2025

1. World-Class Speakers

Hear from Python leaders, innovators, and creators. The lineup includes renowned speakers who will share their insights on Python's role in shaping industries like AI, web development, and scientific research.

2. Engaging Talks and Panels

With a mix of technical talks and panel discussions, PyCon Italia will cover topics ranging from Python best practices to its applications in emerging technologies. These sessions cater to both beginners and advanced users.

3. Hands-On Workshops

Interactive workshops provide the chance to learn by doing. From Python basics to advanced frameworks, these sessions are designed to help you level up your skills.

4. Networking Opportunities

From coffee breaks to evening socials, PyCon Italia is the perfect place to connect with like-minded individuals, form collaborations, and expand your professional network.

5. Sprints and Open-Source Contributions

Join the developer sprints to contribute to open-source projects, collaborate with other Pythonistas, and give back to the community.

Who Should Attend?

• Developers looking to enhance their Python knowledge.

• Educators eager to explore innovative ways of teaching Python.

• Data Scientists and Analysts interested in Python’s latest trends.

• Students and Beginners wanting to kickstart their Python journey.

Registration and Tickets

Visit the official PyCon Italia 2025 website (https://www.python.org/events/) for ticket information and registration. Early bird discounts are available, so secure your spot today!

How to Get Involved

PyCon Italia thrives on community participation. Here’s how you can contribute:

• Submit a Proposal: Share your expertise by presenting a talk or workshop.

• Volunteer: Play a vital role in making the event a success.

• Become a Sponsor: Showcase your company’s commitment to the Python community.

Experience Italy Beyond the Conference

Attending PyCon Italia is not just about Python—it’s also a chance to experience the beauty and culture of Italy. Explore historic landmarks, savor world-famous cuisine, and soak in the vibrant atmosphere of the host city.

Register : PyCon Italia 2025

For live updates join : https://chat.whatsapp.com/L53kHn6EtoOALlVbqLP10L

Join the Celebration

PyCon Italia 2025 is more than a conference; it’s a celebration of the Python community and its impact on technology and innovation. Whether you're attending in person or virtually, you’re guaranteed to leave with new knowledge, connections, and inspiration.

Mark your calendar and get ready to join Python enthusiasts from across the globe for an unforgettable event. See you at PyCon Italia 2025!

Read More

PyCon US 2025: A Celebration of Python, Community, and Innovation

 

The much-anticipated PyCon US 2025 is just around the corner, promising to bring together Python enthusiasts, developers, educators, and community leaders from all corners of the globe. Whether you're a seasoned Pythonista or a beginner curious about the language, this year’s PyCon is set to inspire, educate, and foster connections that will last a lifetime.

Event Details

• Dates: May 14–22, 2025

• Location: Pittsburgh, Pennsylvania, USA

• Theme: "Empowering the Future with Python"

• Hybrid Format: Attend in person or virtually

Why PyCon US Matters

PyCon is not just a conference; it’s the heartbeat of the Python community. Organized by the Python Software Foundation (PSF), PyCon offers a platform for:

• Sharing cutting-edge developments in Python.

• Learning from workshops, tutorials, and talks.

• Networking with industry experts and like-minded enthusiasts.

• Supporting open-source projects and initiatives.

This year, the conference theme, "Empowering the Future with Python," highlights Python’s role in driving innovation in fields like AI, data science, web development, and beyond.

Key Highlights of PyCon US 2025

1. Inspiring Keynote Speakers

Expect thought-provoking keynotes from industry leaders and visionaries who are shaping the future of technology with Python. Past PyCons have featured speakers like Guido van Rossum (Python’s creator), and 2025 is expected to deliver equally stellar insights.

2. Hands-On Workshops and Tutorials

Sharpen your Python skills with hands-on sessions led by experts. From beginner-friendly workshops to advanced tutorials on machine learning, web frameworks, and data visualization, there’s something for everyone.

3. Developer Sprints

The legendary sprints return! Join open-source contributors to collaborate on Python projects, contribute to your favorite libraries, and give back to the community.

4. Expo Hall and Job Fair

Explore the latest tools, frameworks, and services in the Expo Hall, and connect with top tech companies at the Job Fair. It’s a great opportunity to discover career opportunities and gain insights into industry trends.

5. Community and Networking Events

From meetups to dinners, PyCon is packed with opportunities to build meaningful connections. The Python community’s welcoming and inclusive spirit makes these events a must-attend.

Who Should Attend?

PyCon US 2025 is open to everyone, including:

• Developers: Stay updated on the latest Python features and trends.

• Educators: Discover new ways to teach Python effectively.

• Data Scientists: Learn how Python is advancing the field of analytics.

• Students and Beginners: Start your Python journey in a supportive environment.

How to Register

Visit the official PyCon US 2025 website ([Insert URL]) for registration details. Early bird discounts are available, so don’t wait too long!

Register : PyCon US 2025

Get Involved

Want to contribute? Here’s how you can get involved:

• Submit a Talk or Workshop: Share your knowledge with the community.

• Volunteer: Help make PyCon 2025 an unforgettable experience.

• Sponsor the Event: Showcase your organization’s support for Python.

Looking Ahead

As Python continues to grow and evolve, PyCon US 2025 serves as a reminder of the language’s incredible journey and the vibrant community that sustains it. Whether you’re attending to learn, share, or simply connect, this year’s PyCon promises to leave you inspired and energized.

Mark your calendar, pack your bags (or set up your virtual space), and get ready to immerse yourself in all things Python. See you at PyCon US 2025!

---

Read More

Cartoonized Images using Python

 

import cv2

import numpy as np

def cartoonize_image(img_path, save_path):

    img = cv2.imread(img_path)

    if img is None:

        raise ValueError("Could not read the image")

    

    data = np.float32(img).reshape((-1, 3))

    _, labels, centers = cv2.kmeans(data, 8, None,

        (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 20, 0.001),

        10, cv2.KMEANS_RANDOM_CENTERS)

    quantized = np.uint8(centers)[labels.flatten()].reshape(img.shape)

    

    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    edges = cv2.adaptiveThreshold(cv2.medianBlur(gray, 7), 255,

        cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 9, 2)

    

    cartoon = cv2.bitwise_and(quantized, quantized, mask=edges)

    cv2.imwrite(save_path, cartoon)

    return cartoon

if __name__ == "__main__":

    try:

        cartoonize_image("coldplay.jpg", "cartoon_output.jpg")

        print("Image cartoonized successfully!")

    except Exception as e:

        print(f"Error: {e}")

Read More