Machine Learning with Python Training (beginner to advanced)

Machine Learning with Python Training (beginner to advanced)

What you’ll learn

• Deep dive into the world of Machine Learning (ML)
• Apply Python for Machine Learning programs
• Understand what is ML, need for ML, challenges & application of ML in real-life scenarios
• Types of Machine Learning
• Components of Python ML Ecosystem
• Anaconda, Jupyter Notebook, NumPy, Pandas, Scikit-learn
• Regression analysis
• scikit-learn Library to implement Simple Linear Regression
• Multiple Linear Regression and Polynomial Regression
• Logistic Regression
• What is Classification, Classification Terminologies in Machine Learning
• What is KNN? How does the KNN algorithm work?
• What is a Decision Tree and Implementation of Decision Tree
• SVM and its implementation
• What is Clustering and Applications of Clustering
• Clustering Algorithms
• K-Means Clustering and K-Means Clustering algorithm example
• Hierarchical Clustering
• Agglomerative Hierarchical clustering and how does it work
• Woking of Dendrogram in Hierarchical clustering
• Implementation of Agglomerative Hierarchical Clustering
• Association Rule Learning
• Apriori algorithm and Implementation of Apriori algorithm
• Introduction to Recommender Systems
• Content-based Filtering
• Collaborative Filtering
• Implementation of Movie Recommender System