Day 7 of becoming an AI/ML Engineer 💻 Today’s topic: Dictionaries, methods, and functions in Python Learned how to store and access data using key–value pairs. Building strong fundamentals every day! #Python #AI #ML #LearningInPublic #StudentJourney

Today I explored Linear Regression in Machine Learning — from simple to multiple and polynomial models. Understanding how different features shape predictions step by step. 📊 Building a strong foundation, one concept at a time. 🔗 GitHub: https://lnkd.in/g4mDK4fM #MachineLearning #LinearRegression #DataScience #LearningJourney #AI #Python

One rogue data point can completely skew your machine learning model. Check out this quick, visual guide breaking down the mechanics of Outlier Detection (IQR vs. Z-Score) and when you should cap vs. drop your data! #Part1 #DataScience #MachineLearning #DataCleaning #Python #DataEngineering #AI #TechEducation

Machine learning sounds intimidating. It really isn't. Here's how I like to think about it — You know how you get better at spotting bad fruit at the grocery store over time? You've seen enough bad bananas to just... know. ML models do the same thing. You show them thousands of examples, they learn the pattern, and then they start making their own calls. That's it. That's the magic. What part of ML have you always found confusing? Drop it below #MachineLearning #DataAnalytics #Python #DataScience #MLforBeginners

✨ A New Beginning in My AI/ML Journey As part of the Industry Immersion Program by MeetMux, Day 3 marked my transition from setup to execution. 🔹 What I tackled today: Built a basic data pipeline using Python, NumPy, and Pandas — focusing on how data is processed, structured, and analyzed. 🔹 What I learned : The concept of vectorization in NumPy — instead of using loops, operations can be applied to entire datasets at once, making computations significantly faster. This is a core technique used in real-world AI systems. 🔹 My goal: To continue building a strong foundation in data handling and move towards implementing real-world machine learning models by the end of this week. 🔗 My Work (GitHub): https://lnkd.in/gQNYJ8ce #AI #MachineLearning #Python #NumPy #Pandas #IndustryImmersion #LearningInPublic #MeetMux

Starting my journey in Machine Learning! Today, I worked on a simple Linear Regression model using Python and Scikit-learn. 🔹 Created a dataset with input (X) and output (y) 🔹 Trained the model using Linear Regression 🔹 Predicted the output for a new input value This small step helped me understand how machines can learn patterns from data and make predictions. Key takeaway: Even a simple model can give powerful insights when the relationship between data is clear. Looking forward to exploring more concepts like classification, model evaluation, and real-world datasets! #MachineLearning #Python #DataScience #LearningJourney #AI #StudentLife

Day 63 of my AI/ML class Today I learned about bayes algorithms and some of its examples and graphs from Digital Pathshala #python #AI #Learningjourney #Digitalpathshala

Built a Machine Learning obesity prediction app in Python and Flask, reaching 76.6% accuracy. This project was a strong exercise in model building, evaluation, and deploying ML in a practical application. Repo: https://lnkd.in/dnq6kirn #MachineLearning #Python #Flask #DataScience #AI #ModelDeployment #HealthTech

Here’s a quick demo of our AI-powered Deepfake Detection System built at Hack Arya Verse 2.0 🚀 ->The system can detect: -Fake vs real images -Deepfake videos -AI-generated text -Fake voice/audio -News credibility ⚙️ Built using: Python, Flask & AI/ML models #DeepfakeDetection #AI #HackAryaVerse2 Arya College of Engineering and IT JECRC University JECRC

Built a Machine Learning project to classify Muffin vs Cupcake using SVM, Decision Tree, and KNN. Explored data, trained models, and evaluated performance. 🍰📊 #MachineLearning #Python #DataScience #AI https://lnkd.in/d8Z5EiDc