This workshop is a primer designed for audiences of all backgrounds. Although, prior experience with either coding or statistics will be beneficial. All topics are taught with mathematical explanation and hands-on exercises to implement the theory.
Use cases Covered - Churn prediction - Human Resource, Customers, etc. Loan default prediction Real estate pricing estimation Health care - Cancer classification Image - classifying type of apparel Text - Predicting the next word in a sentence
Trainer - Siddhant Wade Siddhant is a consultant for data products and the curator of Big Data Mumbai. Using data-driven tech to power products is his passion. He is a visiting faculty across campuses in Mumbai and has helped hundreds of students and professionals understand analytics and ML at a deeper level.
Workshop Modules -
Statistical Modelling + Linear Algebra basics Understanding Machine Learning How ML capability is delivered in products The Cloud eco-system for ML-enabled development and deployment Types of analytics practices - Descriptive, Diagnostic, Prescriptive, Predictive. Introduction to tools - Python, Anaconda, Jupyter, Google Colab, etc.
Python: Syntax basics and functionalities Data Pre-processing using Pandas Data Visualisation using Matplot Exploratory Data Analysis
Introduction to classical Machine Learning Linear Models for prediction Linear Models for classification Understanding why models fail Understanding the great Bias Variance Tradeoff Tuning models to perform better - Regularisation, Bootstrapping, Bagging, etc. Tuning data to increase efficiency - Dimensionality, PCA, Normalisation.
Introduction to complex models Implementing Decision Trees for classification Why do decision trees fail? Optimizing for performance? Ensembling and Bootstrapping Alternatives to decision trees The IRON-MAN of ML models - SVM
Introduction to Deep Learning Mathematics of neural networks Introduction to Tensorflow and Keras Implementing neural networks Implementing deep neural nets Classification and prediction with Neural Networks Generative Adversarial Networks
Career-paths in Data Science Cloud platforms and tools to implement machine learning Introduction development kits and deployment strategies Learning resources and strategies
Date: 28th - 29th Sep 2019 (Sat-Sun) Venue: Rise Mumbai, Peninsula Business Park, Lower Parel, Mumbai. Time: 10 AM - 5 PM