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PYTHON_ML_DS

Module 1 - Python Programming

  1. Intro to Python
  2. Data Structures in Python (List, Tuple, Set, Dictionary)
  3. Control Statements (Decision and Loops)
  4. Functions and Modules

Module 2 - Python for Data Science

  1. Numpy
  2. Pandas
  3. Missing Value Treatment
  4. Exploratory Data Analysis (Matplotlib, Seaborn and Plotly)

Module 3 - Machine Learning

  1. K - Nearest Neighbours
  2. Linear Regression
  3. Logistic Regression
  4. Gradient Descent
  5. Decision Trees
  6. Support Vector Machines
  7. K - Means
  8. Principal component Analysis

Module 4 - Case Studies

  • Car Price Prediction (Regression)
  • Airline Sentiment Analysis (NLP - Classification)
  • Spam Detection (NLP - Classification)
  • Adult Income Prediction (Classification)
  • Web App Development + Serialization and Deserialization http://18.217.168.12:8501/
  • Deployment -> Open this link to learn more http://18.217.168.12:8502/

Module 5 - Deep Learning

  • Coming Soon (in July)

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