Live Class

Batch Starts : October 1, 2021

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.

#### Class 1: Introduction to Machine Learning

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

#### Class 1

##### October 1, 2021 | 01:00 PM

#### Introduction to Machine Learning

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

#### Class 2: 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.

#### Class 2

##### October 5, 2021 | 01:00 PM

#### 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.

#### Class 3: 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

#### Class 3

##### October 8, 2021 | 01:00 PM

#### 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

#### Class 4: 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.

#### Class 4

##### October 12, 2021 | 01:00 PM

#### 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.

#### Class 5: 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.

#### Class 5

##### October 15, 2021 | 01:00 PM

#### 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.

#### Class 6: 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

#### Class 6

##### October 19, 2021 | 01:00 PM

#### 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

#### Class 7: 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

#### Class 7

##### October 22, 2021 | 01:00 PM

#### 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

#### Class 8: 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

#### Class 8

##### October 26, 2021 | 01:00 PM

#### 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

#### Class 9: Capstone Project - Machine Learning

###### Capstone Project - Machine Learning

#### Class 9

##### October 29, 2021 | 01:00 PM

#### Capstone Project - Machine Learning

###### Capstone Project - Machine Learning

Notebook

Enroll in unlimited courses, get a personalized schedule and never miss a live class with our timely reminders

Enroll in unlimited courses, get a personalized schedule and never miss a live class with our timely reminders

Enroll in unlimited courses, get a personalized schedule and never miss a live class with our timely reminders

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These classes are very good, mentor answers all queries during live session. The reference material is very good to revise concepts and to practice quiz.

In **Explorer** subscription type you can attend free courses/live classes/sessions any number of times for 1 month (from the date of signup).

In **Coder **subscription type you can attend all courses/live classes/sessions (both free and paid) unlimited times for 1 year. Additionally you can choose and attend 1 Project session of your interest.

In **Hacker** subscription type you can attend all courses, projects/live classes/sessions unlimited times for 1 year. Also you can attend all project sessions.

Specialisations are career paths. They guides you about the particular career path, why its important, what skills you need to learn in that career path, classes and projects available in that career path etc.

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