FREE Machine Learning Course Part 6 🔥 | REAL Projects + 40 Datasets | Practical Training | 2026 скачать в хорошем качестве

FREE Machine Learning Course Part 6 🔥 | REAL Projects + 40 Datasets | Practical Training | 2026

Machine Learning is NOT just theory — this is where REAL practical learning gets deeper 🔥 Welcome to the FREE Full Machine Learning Course – Part 6 (2026) 🚀 In this video, you’ll move one step closer to becoming an industry-ready ML professional with hands-on implementation, real datasets, and practical workflows explained in the simplest way possible. 👉 If your goal is to become a Machine Learning Engineer, Data Scientist, or AI Professional, this video is a MUST-WATCH. ✅ What You’ll Learn in FREE ML Course – Part 6 ✔ Advanced real-world Machine Learning implementation ✔ Working with industry-level datasets ✔ Data preprocessing & feature engineering (practical) ✔ Model building, tuning & evaluation ✔ Understanding model performance ✔ Avoiding common ML mistakes ✔ Production-ready workflow insights ✔ Resume-worthy practical exposure 💼 🔥 100% practical — zero unnecessary theory ⏱️ Timestamps: 00:00 – Introduction & Recap of Previous Session 00:45 – Logistic Regression Theory Overview 02:19 – Linear vs Logistic Regression 03:10 – Predicting Numbers vs Classes 04:00 – Graphical Differences Explained 04:32 – Introduction to Model Evaluation Metrics 05:00 – Why Evaluation is Important 05:25 – Accuracy Score Explained 06:40 – Formula for Accuracy Score 08:15 – Example of Accuracy Calculation 10:05 – Drawback of Accuracy (Imbalanced Data) 11:16 – Introduction to Confusion Matrix 12:30 – Structure of Confusion Matrix 14:05 – True Positive (TP) Explained 16:02 – False Positive (FP) Explained 18:10 – False Negative (FN) Explained 20:05 – True Negative (TN) Explained 22:40 – How to Read a Confusion Matrix 25:10 – Common Mistakes in Interpretation 27:26 – Practical Example: Hospital ML Model 29:15 – Identifying TP, FP, FN, TN 31:40 – Interpreting Model Predictions 33:20 – Understanding Model Errors 34:58 – Precision Score Explained 35:50 – Precision Formula 37:05 – Precision Using Hospital Example 38:31 – Recall Score (Sensitivity) Explained 40:10 – Recall Formula 42:25 – Precision vs Recall 45:00 – When Recall Matters Most 46:35 – Improving Model Sensitivity 48:09 – Assignment: Create a Confusion Matrix 48:20 – Calculate Accuracy, Precision & Recall 48:40 – Final Instructions & Wrap-Up 🎯 Who Should Watch This Video? ✅ Machine Learning beginners ready to level up ✅ Data Science & AI students ✅ Working professionals switching to ML ✅ Python developers ✅ Anyone targeting ML jobs in 2026 📌 Part 6 = Professional Skill Phase If you’ve completed Parts 1–5, this session will push your Machine Learning skills toward job-ready level 🚀 📌▶️ Playlist Links Here: Part 1 -    • FREE 🔥 Full Machine Learning Course 2026 😱...   Part 2 -    • FREE 🔥 Full Machine Learning Course – Part...   Part 3 -    • FREE 🔥 Full Machine Learning Course Part 3...   Part 4 -    • FREE 🔥 Machine Learning Course Part 4 😱 | ...   Part 5 -    • FREE Machine Learning Course Part 5 🔥 | RE...   Part 6 -    • FREE Machine Learning Course Part 6 🔥 | RE...   👉 Highly recommended: Start from Part 1 to build strong ML fundamentals. 👉 LIKE 👍 | SHARE 🔁 | SUBSCRIBE 🔔 👉 Follow the channel for FREE training & upcoming Machine Learning projects 📅 Updated for 2026 | 100% FREE | Industry-Oriented Training 🔥 Want the next part with ADVANCED Machine Learning + Live Projects? Comment 👉 ML Part 7 🚀 #MachineLearning #MachineLearningCourse #MachineLearningFree #MachineLearning2026 #MLCourse #LearnMachineLearning #FreeMLCourse #PracticalMachineLearning #MLTraining #MLProjects #RealWorldML #HandsOnMachineLearning