Machine Learning in Python

Open the doors to a very exciting and most popular fields of Machine Learning.

(3729 Ratings)

This course will introduce you to a very exciting and highly popular Machine Learning. You'll get applied experience in major areas of Machine Learning which include Prediction, Classification, Clustering and Information Retrieval. Learn to analyze large & complex datasets, build systems that adapt and improve over a period of time, and develop smart applications to make predictions from data.


Importance of Python

Describe the basics of the Python programming language

Install Python and write your first program

Use variables and constants to store, retrieve and calculate information

Utilize core programming tools such as functions and loops

Accomplish multi-step tasks like sorting or looping using tuples

Create programs that are able to read and write data from files

Store data as key/value pairs using Python dictionaries

Using Scikit Learn in Machine Learning Techniques like Regression, Classification, Clustering, Recommender Systems

Doing basic project in Python

Select and process the data

Process data using Graphs Library in Python

Creating capstone project on Machine Learning using TensorFlow in Python

Usage of Python Libraries

Live Classes

  • Course Walkthrough
  • Overview to Machine Learning
  • Artificial Intelligence Vs Machine Learning Vs Deep Learning
  • Machine Learning: Python Libraries
  • Supervised Vs. Unsupervised Learning
  • Module Quiz: Machine Learning Overview

  • Introduction to Regression
  • Various Regression Techniques: Linear, Polynomial, Stepwise, Ridge, Lasso and ElasticNet
  • Linear Regression using Python
  • Linear Regression Techniques: Slopes And Intercept
  • Linear Regression using SKLEARN Coding
  • Demo Machine Code: Linear Regression using SKLEARN Coding
  • Demo Code Explaination: Linear Regression using SKLEARN Coding
  • Errors in Linear Techniques
  • R-Squared or Coefficient of Determination
  • Multiple Linear Regression (MLR)
  • Polynomial Vs. Non Linear Regression
  • Module Quiz: Regression in Python

  • Introduction to Classification
  • K-Nearest Neighbor(KNN) Algorithm for Machine Learning Introduction
  • Working with K-Nearest Neighbor(KNN) Algorithm for Machine Learning
  • Evaluation Metrics for Classification
  • Machine Learning Decision Tree Classification Algorithm
  • Support Vector Machine (SVM) Algorithm in Machine Learning
  • Machine Learning Random Forest Algorithm
  • Module Quiz: Classification

  • Clustering Algorithms in Machine Learning
  • Clustering Vs Classifications: Machine Learning
  • K means Clustering - Introduction
  • Module Quiz: Clusterin in Machine Learning

  • Understanding Recommender Systems in Machine Learning
  • Content-based Filtering: Recommendation Systems
  • Collaborative Filtering: Recommendation Systems
  • Module Quiz: Recommender Systems in Machine Learning

  • Introduction to the Project: Guess Game
  • Project Implementation: Undestanding the Concepts to Build Guess Game
  • Proejct Code: Guess Game Using Python

  • Understanding Python Libraries
  • Three-dimensional Plotting in Python using Matplotlib
  • Tri-Surface Plot in Python using Matplotli
  • Professional 3D Plotting in Matplotlib - 3D Plot Game

  • Understanding Machine Learning Concepts
  • Flowcharts - Problem Solving with Python
  • Deep Learning: Training and Testing the Network with Tensorflow and Keras
  • Tensorflow and Keras For Neural Networks and Deep Learning
  • Final Certification Quiz; Complete Course
  • Machine Learning Final Assignment

  • Machine Learning Live Class with Google Expert

  • Logistic Regression for Malignancy Prediction in Cancer (Breast Cancer)
  • Spam Mail Prediction using Machine Learning with Python
  • Personal Assistant
  • Weather recommendation system

  • Understanding Machine Learning Workflow
  • Decoding Model Selection for Machine Learning
  • Understanding Overfitting in Machine Learning
  • Understanding Underfitting in Machine Learning
  • Understanding the Bias-Variance Tradeoff
  • Introduction to Dimensionality Reduction for Machine Learning
  • Gradient Descent algorithm and its Variants

  • Hands-On-Guide To Machine Learning Model Deployment Using Flask

  • GitHub Tutorial and Profile Buidling


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Machine Learning in Python


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  • 61 Lessons
  • 00:00:00 Hours On demand videos
  • Lifetime Video Access
  • Certificate of Completion
  • Approx. 3 Months to Complete
  • Live Classes
  • Quizzes and Assignments
  • No Prior Experience Required
  • Top 50 Interview Question
  • Resume Building