Lec-50: Single Layer Neural Network | Machine Learning
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47.2K viewsApr 7, 2025
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Lec-37: Ridge and Lasso Regression | Machine Learning
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Lec-28: kNN(k Nearest Neighbour) Numerical Example | Supervised Learning | Machine Learning
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Lec-28: kNN(k Nearest Neighbour) Numerical Example | Supervised Learning | Machine Learning
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Input Gate in LSTM | Deep Learning
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4.9K views2 months ago
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Lec-46: Principal Component Analysis (PCA) Explained | Machine Learning
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Lec-48: Perceptron Learning in ANN | Single Layer Perceptron Model
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Lec-39: Multiple Linear Regression (MLR) | Machine Learning
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Lec-40: Support Vector Machines (SVMs) | Machine Learning
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9:53
Lec-38: Mean Squared Error (MSE) | Machine learning
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Lec-42: Linear Discriminant Analysis (LDA) | Machine Learning
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Lec-49: What is Multilayer Perceptron (MLP)? | How It Works in Machine Learning
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Lec-43: Bias & Variance Tradeoff Explained: How to Fix Overfitting & Underfitting?
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Lec-41: Numerical Explanation on SVM | How Support Vector Machine Algorithm Works
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Lec-57: Uncertainty probabilistic inference (Markov Model) | Artificial Intelligence
120K viewsApr 12, 2025
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Lec-58: Introduction to Hidden Markov Model | Artificial Intelligence
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Lec - 23 : Clustering in Data Mining Explained | Top Clustering Methods You MUST Know!
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Lec-14: Hierarchical Clustering | Agglomerative vs Divisive with examples
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Lec-6: Linear Regression Vs. Logistic Regression | Supervised Learning | Machine Learning
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DBSCAN Clustering Algorithm with Numerical example
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Lec-18: Random Forest 🌳 in Machine Learning 🧑‍💻👩‍💻
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Lec-25: BAGGING vs. BOOSTING vs STACKING in Ensemble Learning | Machine Learning
234K viewsDec 20, 2023
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Lec-27: Pearson's Correlation Coefficient | Supervised Learning | Data Science & Machine Learning
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