Python With Machine Learning

Introduction To DataScience
  • Getting started with ANACONDA

  • Downloading and installing ANACONDA managing environment and instructions on ANACONDA, navigating the SPYDER and JUPYTER notebook interface.

  • Downloading datasets, data exploration and analysis, presenting your data.

  • Python for Data Science.

    • Data types

    • Control Structures

    • Functions

    • User Defined Functions

    • Python Packages

    • Numpy,Pandas,Matplotlib,TensorFlow

Regression Analysis
  • Categories of machine learning

  • Linear Regression Models

  • Logistic Regression Models

  • Neural Network Models

  • Clustering Concepts

  • K-Means Clustering

Support Vector Machines
Random Forests (Ensemble Machine Learning)
Decision Trees
Unsupervised Learning. (Dimensionality Reduction Techniques)
Principle Component Analysis (PCA)
K-Nearest Neighbors