MACHINE LEARNING

COURSE DESCRIPTION

This machine learning tutorial gives you an introduction to machine learning along with the wide range of machine learning techniques such as Supervised ,Unsupervised and Reinforcement learning. You will learn about regression and classification models, clustering methods .We will start from the beginning like python , API ,deployment in AWS, AZURE,GCP,HEROKU. You will learn Statistics, all Machine Learning Algorithm. 

COURSE OVERVIEW

• Introduction to Machine Learning
• STATISTICS
  • Statistics Basic
  • Statistics Advance
• CORE PYTHON
• ADVANCE PYTHON
• Numpy
• Pandas
• Matplotlib
• Sklearn
• EDA
• Probability
• Seaborn
• Feature Engineering
• Underfitting Overfitting
• ALGORITHMS
  • Linear Regression
  • Ridge and Lasso Regression
  • Multiple Linear Regression
  • Multi Collinearity
  • Logistic Regression
  • Decision Tree
  • SVM
  • Naive Bayes
  • kNN
  • Clustering
    • K – means Clustering
    • Mean Shift Clustering
    • DBSCAN
    • Agglomerative Hierarchical Clustering
    • EM Clustering
  • K-Means
  • Random Forest
  • Dimensionality Reduction Algorithms
  • Gradient Boosting algorithms
    • GBM
    • XGBoost
    • LightGBM
    • CatBoost
• Pruning Algorithm
• Model Building
• Model Deployment on Google Colab, AWS, Azure.
• 20 End to End Project