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Define Goal : PRODUCTS or ALGORITHMS
Linear Algebra (Matrix, Vector)
Statistics
Probability
Numpy
Pandas
Supervised vs Unsupervised vs Reinforcement
Linear RegressionDefine Goal : PRODUCTS or ALGORITHMS
Linear Algebra (Matrix, Vector)
Statistics
Probability
Numpy
Pandas
Supervised vs Unsupervised vs Reinforcement
Linear Regression, Logistic Regression, Clustering
KNN (K Nearest Neighbours)
SVM (Support Vector Machine)
Decision Trees
Random Forests
Overfitting, Underfitting
Regularization, Gradient Descent, Slope
Confusion Matrix
Handling Null Values
Standardization
Handling Categorical Values
One-Hot Encoding
Feature Scaling
Scikit learn
Matplotlib
Tensorflow for DL
Machine Learning Course by Google