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machinelearning's Introduction

Practical Machine Learning with Python

Content

  1. Probability & Statistics Intuition
  2. Python
  • Numpy
  • Pandas
  • Matplotlib
  1. Regression
  • Linear Regression
  • Polynomial Regression
  • Multiple Regression
  1. Classification
  • Logistic Regression
  • K Nearest Neighbour
  • Support Vector Machine
  • Descion Tree
  • Random Forest
  • Navie Bayes
  1. Natural Language Processing
  • Restaurants Sentiment Analysis
  1. Unsupervised Learning
  • K Means Clustering
  1. Watson Studio
  • Watson Machine Learning
  • Deploying Machine Leanring model
  1. Projects
  • Movie Review System (Kaggle)
  • Diabetes health moniter system (Deployed in IBM Wastson Studio)
  • Gender Classification using Machine Learning

https://www.kaggle.com/uciml/pima-indians-diabetes-database/data

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