Machine Learning Journey at Codveda Technologies The project involved training and tuning hyperparameters such as the number of trees and max depth, evaluating performance using cross-validation and classification metrics (precision, recall, and F1-score), and analyzing feature importance to understand what drives predictions. Tools used: Python, scikit-learn, pandas, matplotlib. #CodvedaInternship #CodvedaTech #MachineLearning #python

Supervised and Unsupervised Learning. With Supervised learning there is a definite outcome, whereas Unsupervised learning the whole point is to see what you have, and try to make sense of it. #data #python #learning

Today I fixed and improved a small image-processing script in Python using OpenCV to visualize an image histogram + CDF properly. Added correct path handling, file checks, and clean plotting—so it runs reliably across systems. If you’re learning Computer Vision, this is a great mini-exercise to understand pixel intensity distribution. #Python #OpenCV #ComputerVision #ImageProcessing #NumPy #Matplotlib #LearningByDoing

Machine Learning is no longer just a "buzzword"-it is a fundamental tool for solving complex problems and driving data-informed decisions. This course provided a comprehensive deep dive into the end-to-end ML workflow using Python. #MachineLearning #Python #DataScience #ArtificialIntelligence #ContinuousLearning

Mastering machine learning sounds cool until you're buried in math, lost in algorithms, and wondering what Python package you're supposed to install next. If you've ever: - Opened a tutorial and closed it 10 minutes later - Felt like everyone else already gets it - Wondered where you were supposed to start... This blog post can help you. It breaks down the real path to getting started with machine learning using Python. #MachineLearning #Python #AI #DataScience #RheinwerkComputingBlog #RheinwerkComputingInfographic Take your first (or next) step here: https://hubs.la/Q03-nkwR0

Start strong: XGBoost refinements in recent versions enhance scaling for predictive modeling, handling larger datasets effectively. Documentation updates: https://lnkd.in/gBMUMQrA In ML work, these improvements support accurate tabular predictions. Watching boosting advancements? Views? #XGBoost #MachineLearning #Python #DataScience #AIProgress

Built a machine learning regression model to predict California housing prices using XGBoost and evaluated its performance through an actual vs predicted comparison. The project focuses on model training, performance evaluation, and a simple Streamlit interface for making predictions. Tech stack: Python, Pandas, NumPy, Scikit-learn, XGBoost, Streamlit. #MachineLearning #DataScience #Python #XGBoost #Regression #ScikitLearn #Streamlit #LearningByDoing #BuildInPublic

I wish I had this roadmap when I started Machine Learning. So I built a simple 6-slide guide that shows: • Where to start • What to learn next • How Python fits into ML • How to avoid beginner mistakes If you’re learning ML in 2026, this is for you 👇 Swipe | Save | Share #MachineLearning #Python #SelfLearning #AIJourney #TechCareers#MLBeginner #PythonLearning #LearnMachineLearning #TechSkills #SelfLearning

🚢 Titanic Survival Prediction – Machine Learning & Streamlit ✅ Developed and deployed a user-friendly Streamlit web application to predict Titanic survival using Machine Learning, with clear model comparison and performance insights GITHUB LINK : https://lnkd.in/gaptG8kv STREAMLIT.IO LINK : https://lnkd.in/g6R6TwAd #DataScience #MachineLearning #Streamlit #Python #MLProject #LearningJourney #CareerRestart

Learning Update | Python for Generative AI Today, I revisited key Python concepts essential for Machine Learning and Generative AI and organized my progress into a structured GitHub repository. The repository covers Python libraries, statistical analysis (univariate, bivariate, multivariate), and core Python concepts from an ML/GenAI perspective. I’m looking forward to continuously learning and updating this repository as I grow in the field. Sharing my learning progress here: 🔗 GitHub repository link https://lnkd.in/gHaZa3Zf #Python #MachineLearning #GenerativeAI #LearningInPublic #GitHub