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Lecture 4.2 | Deep Learning | Convolutional neural network | Types of Layers | Case Study #mlt #aktu
Lecture 5.1 | Reinforcement learning | Reinforcement learning in practice | #mlt #aktu #unit5
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Lecture 3.4 | KNN Algorithm In Machine Learning | K Nearest Neighbor | Classification | #mlt #knn
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Lecture 1.13 | Bayesian network | Bayesian Learning | Machine learning techniques #mlt #ml #bayesian
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Lecture 2.2 | Logistic Regression Explained in hindi | logistic regression | #mlt #machinelearning
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Lecture 3.7 | Case-Based Reasoning | Case-Based Learning | Machine learning techniques | #mlt #aktu
Lecture 1.14 | Support Vector Machine (SVM) Explained | Machine learning techniques #mlt #svm #ml
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Lecture 3.1 | Decision Tree Learning | Inductive Bias, Entropy, Gini Impurity, Information Gain #mlt
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Lecture 2.1 | Linear Regression | Simple and Multiple Linear Regression | Explained in Hindi #mlt
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Lecture 1.12 | Decision Tree learning | Decision tree | Machine Learning | #machinelearning #mlt #ai
Lecture 3.5 | Locally Weighted Regression | Instance based learning | Machine learning technique #ml
Lecture 2.4 | Naive Bayes Classifier | Naive bayes classifier with example | Machine learning | #mlt
Lecture 1.4 | Unsupervised Learning | What is unsupervised learning | Machine learning techniques
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Lecture 1.7 | Designing a learning system in machine learning | ML Model #machinelearning #mlt
