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Machine Learning specialization
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Machine Learning

4.8

(819 ratings)

Learn and apply fundamental machine learning concepts in this specialisation, get real-world experience with the capstone project. This specialisation covers concepts like regression, classification, model evaluation, clustering and building machine learning web apps using flask, deploying machine learning model to cloud. All classes are live instructed by mentor accompanied by unique "notebook" to revise and practice the concepts.

Upcoming Batches

Live Session

Nov 8 | 1:00 PM

Features

Shareable Certificate
Earn a Certificate upon completion
100% Online Live Class
Mentor driven live classes
Instant Doubt Resolution
Get your doubt clarified instantly
Practice Material
Get Notebook to revise, practice, test yourself and interact with mentor

What You Will Learn

Goal - Data Science
What you will learn

Machine Learning

  • How to predict using regression analysis
  • Classify things using logistic regression, KNN algos
  • How to evaluate machine learning models
  • How to build and deploy machine learning models to cloud

PREREQUISITE KNOWLEDGE
  • Basic understanding of Python Programming

Machine Learning Batch Schedule

Batch Starting at
Introduction to Machine Learning

Understanding limitations of algorithm and need of machine to learn, Type of Machine Learning, Supervised and Unsupervised Learning..

08 Nov | 01:00 PM | 90 min

08 Nov | 01:00 PM | 90 min
Simple Linear Regression

Supervised learning, Understanding Linear Regression, Relation between variables, Correlation, Best Fit Line, line equation, best fit line, Sklearn, train test split, case study on simple linear regression..

11 Nov | 01:00 PM | 90 min

11 Nov | 01:00 PM | 90 min
Multiple Linear Regression

Need of multiple regression, multicollinearity, multiple independent variables and advantage of multiple over simple linear regression, case study on multiple linear regression.

15 Nov | 01:00 PM | 90 min

15 Nov | 01:00 PM | 90 min
Logistic Regression

Understanding classification , Regression vs classification, Introduction to logistic regression, sigmoid function, finding equation of logistic regression, converting continuous values to binary, logistic regression equation, case study on logistic regression..

18 Nov | 01:00 PM | 90 min

18 Nov | 01:00 PM | 90 min
Model Evaluation

Finding out how to measure whether a good model is developed or bad. Using Model evaluation such as Classification score, Confusion Matrix, Precision, Recall and Accuracy score..

22 Nov | 01:00 PM | 90 min

22 Nov | 01:00 PM | 90 min
K Nearest Neighbors

Extending classification for multiple classes using K nearest neighbor, what is K Nearest Neighbors, Defining value of K and optimum value of K, case study on KNN.

25 Nov | 01:00 PM | 90 min

25 Nov | 01:00 PM | 90 min
K Means Clustering - Unsupervised Learning

Looking at unsupervised learning, introduction to clustering algorithm, K means clustering algorithm and how to decide value of K, Elbow method, case study on K Means Clustering.

29 Nov | 01:00 PM | 90 min

29 Nov | 01:00 PM | 90 min
Flask - Deploying ML Apps on Cloud Service

Basics of web development, Html, CSS, Intro to flask, Deploying web app using flask Case study: Deploy a ML apps using flask.

02 Dec | 01:00 PM | 90 min

02 Dec | 01:00 PM | 90 min
Capstone Project - Machine Learning

Capstone Project - Machine Learning.

06 Dec | 01:00 PM | 90 min

06 Dec | 01:00 PM | 90 min
Certificate

Machine Learning


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