Fundamentals of Machine Learning [Hindi] [Python]

Topic: Fundamentals of Machine Learning [Hindi][Python] Chapter - Introduction to Machine Learning - Machine Learning? - Types of Machine Learning Chapter - Data Preprocessing - Null Values - Correlated Feature check - Data Molding - Imputing - Scaling - Label Encoder - On-Hot Encoder Chapter - Supervised Learning: Regression - Simple Linear Regression - Minimizing Cost Function - Ordinary Least Square(OLS), Gradient Descent - Assumptions of Linear Regression, Dummy Variable - Multiple Linear Regression - Regression Model Performance - R-Square - Polynomial Linear Regression Chapter - Supervised Learning: Classification - Logistic Regression - K-Nearest Neighbours - Naive Bayes - Saving and Loading ML Models - Classification Model Performance - Confusion Matrix Chapter: UnSupervised Learning: Clustering - Partitionaing Algorithm: K-Means Algorithm, Random Initialization Trap, Elbow Method - Hierarchical Clustering: Agglomerative, Dendogram - Density Based Clustering: DBSCAN - Measuring UnSupervised Clusters Performace - Silhouette Index Chapter: UnSupervised Learning: Association Rule - Apriori Algorthm - Association Rule Mining Chapter: Non-Linear Supervised Algorithm: Decision Tree and Support Vector Machines - Decision Tree Regression - Decision Tree Classification - Support Vector Machines(SVM) - Classification - Kernel SVM, Soft Margin, Kernel Trick Chapter - Natural Language Processing Below Text Preprocessing Techniques with python Code - Tokenization, Stop Words Removal, N-Grams, Stemming, Word Sense Disambiguation - Count Vectorizer, Tfidf Vectorizer. Hashing Vector - Case Study - Spam Filter Chapter - Deep Learning - Artificial Neural Networks, Hidden Layer, Activation function - Forward and Backward Propagation - Implementing Gate in python using perceptron Stay tuned with us.