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AML

Numpy

  1. Basics of numpy
  2. Initializing a numpy array
  3. Accessing elements and slicing
  4. Array Manipulation
  5. Numpy Arithmetics
  6. Mulitple Array Manipulation
  7. Exercise Problems
  8. MatPlotLib
  9. Other Useful Numpy Functions

Pandas

  1. Pandas Series
  2. Series Operations
  3. Pandas Dataframe
  4. Dataframe Operations
  5. Handling Missing Values
  6. Loading and Saving Data

Data Preprocessing

  1. Handling Missing Values
  2. Categorical and Textual Data Encoding
  3. Tfid Count Vectorizer - Textual Data Processing
  4. Dimensionality Reduction - PCA

Classical Machine Learning

  1. Ensemble method - Random Forest Classifier
  2. Ensemble method - AdaBoost Classifier
  3. SVM
  4. Pipelines
  5. Hyperparameter Tuning
  6. Cross Validation

Web Scraping with Beautiful Soup

  1. Intro to WebScraping - Extracting elements from webpages
  2. Basics of BeautifulSoup - Tag Navigation
  3. Scraping Google News Data
  4. Scraping using API - weatherapi.com
  5. Scraping using RegEx

Web Scraping using Scrapy

  1. Extracting and Storing Images and Paragraphs
  2. WebCrawling with rules - CrawlSpider

R Programming

  1. Decision Tree
  2. Random Forest

More

  1. PIL - Python Imaging Library
  2. Numpy Array Image Representation
  3. Tesseract module

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Classical Machine Learning Concepts + Basic WebScraping + Numpy and Pandas libraries

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numpy scikit-learn pandas scrapy beautifulsoup webscraping classical-machine-learning

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