🐍 Python Term of the Day: training (AI Coding Glossary) The process of fitting a model’s parameters to data by minimizing a loss function. https://lnkd.in/d94qMaAF

Task 8: Basic Python Chatbot Created a simple chatbot using Python under KODBUD tasks. This improved my understanding of: ✔️if-else logic ✔️String handling ✔️User interaction Learning how logic turns into interaction hashtag #PythonChatbot hashtag #KODBUD hashtag #Learning Python hashtag #Coding Journey

 Machine Learning (ML) Projects in Python      https://lnkd.in/dQbJPANE Contents…     1 Python Interface of the ML Crash Courses (7 Days) 2 Python interface of the ML using CSV and Model Development 3 Pyton Programs to Implement 2D & 3D 4 Pyton Programs to Implement Particle Swarm Optimization (PSO) 5 Pyton Programs to Implement PSO and to Optimize the Rastrigin F. 6 Python Program to Iris flower classification in the ML

Learning Python is hard. Because learning is boring. Instead: • Find a real problem to solve • Take direct action to solve it • Do it with accountability from peers

🚀 Day 03 — Python Learning Journey Today’s learning was all about Python Strings — how Python works with text and how powerful simple text operations can be. Thanku you Saumya Singh ✅ Learned that strings are immutable (cannot be changed after creation) ✅ Understood indexing and slicing to access specific parts of text ✅ Explored string methods to modify and analyze data easily ✅ Practiced f-strings for clean and readable formatting ✅ Learned escape sequences for quotes, tabs, and new lines Small concepts, but very important for writing clean and readable programs. Step by step, consistency is building confidence in coding. 💻✨ #Python #LearningJourney #Coding #PythonBasics #DeveloperJourney #TechCommunity #Developers #OpenToLearn #BuildInPublic #CFBR #PythonLearning #LearnPython #PythonDeveloper #CodingJourney #ProgrammingLife #CodeNewbie

📸 Image Dataset Downloader using Python Developed a Python-based program to automate high-quality image dataset collection using the bing-image-downloader package. 🔹 Downloads multiple high-quality images using a single Python program 🔹 Accepts user-defined search keywords 🔹 Efficiently collects images in bulk 🔹 Automatically organizes images into structured folders 🔹 Supports dataset preparation for Machine Learning and Computer Vision applications This project strengthened my understanding of efficient data collection and dataset preparation workflows in Artificial Intelligence projects 🚀 #Python #ImageDataset #bing_image_downloader #ArtificialIntelligence #MachineLearning #ComputerVision #AIProjects #BCA

  Machine Learning (ML) Projects in Python     https://lnkd.in/dQbJPANE Contents… 1 Python Interface of the ML Crash Courses (7 Days) 2 Python interface of the ML using CSV and Model Development 3 Pyton Programs to Implement 2D & 3D 4 Pyton Programs to Implement Particle Swarm Optimization (PSO) 5 Pyton Programs to Implement PSO and to Optimize the Rastrigin F. 6 Python Program to Iris flower classification in the ML

Python Tool for Review-Driven Regression Testing of ML LLM Outputs Released 📌 Introducing Booktest, a revolutionary Python tool that transforms regression testing for ML and LLM systems by replacing rigid assertions with review-driven, human-in-the-loop evaluations. It captures outputs as markdown, enables diff-based reviews, and uses tolerance metrics to distinguish real regressions from noise-making it ideal for complex, subjective AI outputs in production. 🔗 Read more: https://lnkd.in/dKpXEjxR #Booktest #Python #Regressiontesting #Llmoutputs #Markdownartifacts

🚀 Day 7/50 – DSA with Python | Hashing & Collision Handling Today, I learned Hashing Data Structure and different ways to handle collisions in hash tables by implementing them in Python. 🔹 Topics Covered: ✅ Hashing with Separate Chaining Implemented hash table using list of lists Operations: insert, search, remove Understood how collisions are handled using chaining ✅ Linear Probing Open addressing technique Sequentially checks next available slot Simple but causes primary clustering ✅ Quadratic Probing Uses square increments (i²) Reduces clustering compared to linear probing Learned why some indexes remain empty ✅ Double Hashing Uses two hash functions Second hash function decides step size Helps reduce clustering more effectively 🔹 Key Learnings: Hash tables do not store data in insertion order Collision handling is crucial for performance Separate chaining vs open addressing differences Why correct hash functions matter 📌 Implemented all techniques from scratch to understand internal working clearly. Feeling more confident with Hash Tables and Collision Resolution 💪 On to the next concept tomorrow 🚀 #DSA #Python #Hashing #DataStructures #LearningJourney #Day7

Day 3 of Learning Python Learning from Sheryians AI School Instructor: Akarsh Vyas sir Today Focused On: Loops (for, while) – deeper practice Logic building using loops Nested loop concepts Solved 25+ assignment questions including: Factors in a given range Palindrome check Anagram check Number based pattern logic Loop based problem solving Solved class MCQs after lecture to revise and strengthen concepts. #Python #Learning #SheryiansCodingSchool #Day3 #Loops