Applied Machine Learning

Nov 16, 2019



Knowledge of Python Programming. Experience of working in pandas and jupyter notebooks.

Have you ever wondered how to apply machine learning to business problems? This workshop is specially designed to help learn the concepts, tools and techniques involved. You will go through real-life case studies and experience how this is done in the industry. The focus of this workshop will be on the machine learning pipeline data cleaning, feature engineering, model building and evaluation. You will also learn how to structure a business problem as an ML problem, and then go on to build, select and evaluate the model. The workshop is divided into following major modules:

Pre-requisites Machine Learning for Beginners

  • Knowledge of Python Programming
  • Have experience working in pandas and jupyter notebooks

This is an 8-hour workshop and includes the following modules:

  • Module 0: Introduction
    • What is Machine Learning
    • Types of ML: Supervised, Unsupervised, Reinforcement
    • Types of ML problems: Regression, Classification
  • Module 1: Linear Models
    • Linear Regression
    • Logistic Regression
  • Module 2: Model Evaluation
    • Training and Validation Model
    • Evaluation Metrics – Accuracy, RMSE, ROC, AUC, Confusion Matrix, Precision, Recall, F1 Score
    • Overfitting and Bias-Variance trade-off
    • Regularization (L1/L2)
    • K-fold Cross Validation
  • Module 3: Tree-based Models
    • Decision Trees
    • Bagging and Boosting
    • Random Forest
    • Gradient Boosting Machines
    • Feature Importance
  • Module 4: Model Selection
    • Model Pipelines
    • Feature Engineering
  • Raghav Bali

    Senior Data Scientist

    UnitedHealth Group


    Raghav Bali is a Senior Data Scientist and a published author. He currently works at one the world’s largest health care organizations. His work involves research & development of enterprise-level solutions based on Machine Learning, Deep Learning and Natural Language Processing for Healthcare & Insurance-related use cases. In his previous role at Intel, he was

  • Dipanjan (DJ) Sarkar

    Data Scientist, Published Author & Consultant



    Dipanjan (DJ) Sarkar is a Data Scientist, a published author and a consultant and trainer. He has consulted and worked with several startups as well as Fortune 500 companies like Intel. He primarily works on leveraging data science, advanced analytics, machine learning and deep learning to build large- scale intelligent systems. He holds a master

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