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LLM​

AI (Artificial Intelligence) + ML (Machine Learning)​

DS (Data Science) + DA (Data Analytics) + DE (Data Engineering)​

Courses ML & AI​

Courses - Data​

Others​

  • Statistics and EDA
  • Data Visualization
  • Descriptive Statistics
  • central tendency and variability
  • Inferential Statistics
  • probability, central limit theorem and more to draw inferences
  • Exploratory Data Analysis
  • Hypothesis Testing
  • Case Study - Uber supply demand gap

Introduction to ML 1​

  • Linear Regression
  • predict continuous data values
  • Supervised Classification
  • KNN, Naives Bayes and Logistic Regression
  • Clustering
  • K-Means and Hierarchical Clustering
  • Case Study - Telecom Churn

Introduction to ML 2​

  • Time Series
  • Decision Trees
  • Support Vector Machines
  • Neural Networks
  • Master Feed-forward, Recurrent and Gaussian Neural Networks.
  • Association Rule Mining
  • BIG DATA ANALYTICS
  • INTRODUCTION TO BIG DATA AND HADOOP
  • Understand the basic concepts of Big Data and Hadoop as processing platforms for Big Data
  • MANAGING BIG DATA
  • Learn and use Hadoop ecosystem tools like Sqoop & Hive for data ingestion, extraction and management.
  • INTRODUCTION TO SPARK
  • Understand and use Spark, a fast Big Data processing platform
  • BIG DATA ANALYSIS
  • Learn how to analyze Big Data using SparkR, SparkSQL
  • Domain Electives
  • BFS
  • Learn Customer analytics and Risk Analytics within BFS (Banking and Financial Services)
  • E-commerce
  • Customer marketing analytics and recommendation engines
  • Health care

Model resources​

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  1. Customer Segmentation
  2. Text Classification
  3. Sentiment Analysis
  4. Time Series Forecasting
  5. Recommendation Systems

Courses​

Machine Learning​

Cheatsheet​

NewsLetter & Blogs​

Examples​

https://towardsdatascience.com/how-to-build-a-real-time-fraud-detection-pipeline-using-faust-and-mlflow-24e787dd51fa

Resources​

Questions​