Machine Learning with Python 2025 Vaidhik Batch

Course Instructor Teachnook Team

FREE

Course Overview

Schedule of Classes

Start Date & End Date

Jun 01 2025 - Jul 31 2025

Course Curriculum

1 Subject

Machine Learning with Python 2025 Vaidhik Batch

31 Learning Materials

Python

Class 1

Video

01:20:18

Class 2

Video

01:15:26

Class 3

Video

01:12:21

Class 4

Video

01:08:20

Class 5

Video

01:12:26

Class 6

Video

01:01:58

Class 7

Video

01:15:08

Class 8

Video

01:14:28

Class 9

Video

00:40:57

Class 10

Video

00:59:51

Class 11

Video

01:19:39

Class 12

Video

01:03:06

Recorded Sesssions

Class 1 - Introduction to AI and Machine Learning Setting up your development environment

Video

00:55:52

Class 2 - supervised learning project using scikit-learn during the live session.

Video

01:01:51

Class 3 - linear regression project using scikit-learn during the live session.

Video

01:00:49

Class 4 - Logistic regression, K-Nearest Neighbors, & model evaluation.

Video

00:53:50

Class 5 - classification project using scikit-learn during the live session

Video

00:38:19

Class 6 - decision tree project using scikit-learn during the live session.

Video

00:50:11

Class 7 - Random Forest: Introduction to random forests, bagging, & boosting.

Video

01:44:37

Class 8 - random forest project using scikit-learn during the live session.

Video

00:55:05

Class 9 - unsupervised learning project using scikit-learn during the live session.

Video

01:25:57

Class 10 - Introduction to principal com ponent analysis (PCA) (t-SNE)

Video

00:56:12

Class 11 - dimensionality reduction project using scikit-learn during the live session

Video

00:49:58

Class 12 - SVM project using scikit-learn during the live session.

Video

00:49:15

Class 13 -Introduction to neural networks, backpropagation algorithm, & activation functions.

Video

00:52:05

Class 14 -neural network project using TensorFlow during the live session

Video

00:32:58

Class 15 - deep learning project using TensorFlow during the live session.

Video

00:43:57

Class 16 -Introduction to NLP, text preprocessing, and bag-of-words model.

Video

01:13:10

Class 17 - NLP project using scikit-learn during the live session.

Video

00:41:40

Class 18 - time series analysis project using statsmodels during the live session.

Video

00:32:20

Class 19 - Ensemble Learning: Introduction to ensemble learning, bagging, boosting, and stacking.

Video

00:51:32

Course Instructor

Teachnook Team

577 Courses • 42164 Students

Machine Learning with Python 2025 Vaidhik Batch

Course Overview

Schedule of Classes

Jun 01 2025 - Jul 31 2025

Course Curriculum

Machine Learning with Python 2025 Vaidhik Batch

Python

Class 1

Class 2

Class 3

Class 4

Class 5

Class 6

Class 7

Class 8

Class 9

Class 10

Class 11

Class 12

Recorded Sesssions

Class 1 - Introduction to AI and Machine Learning Setting up your development environment

Class 2 - supervised learning project using scikit-learn during the live session.

Class 3 - linear regression project using scikit-learn during the live session.

Class 4 - Logistic regression, K-Nearest Neighbors, & model evaluation.

Class 5 - classification project using scikit-learn during the live session

Class 6 - decision tree project using scikit-learn during the live session.

Class 7 - Random Forest: Introduction to random forests, bagging, & boosting.

Class 8 - random forest project using scikit-learn during the live session.

Class 9 - unsupervised learning project using scikit-learn during the live session.

Class 10 - Introduction to principal com ponent analysis (PCA) (t-SNE)

Class 11 - dimensionality reduction project using scikit-learn during the live session

Class 12 - SVM project using scikit-learn during the live session.

Class 13 -Introduction to neural networks, backpropagation algorithm, & activation functions.

Class 14 -neural network project using TensorFlow during the live session

Class 15 - deep learning project using TensorFlow during the live session.

Class 16 -Introduction to NLP, text preprocessing, and bag-of-words model.

Class 17 - NLP project using scikit-learn during the live session.

Class 18 - time series analysis project using statsmodels during the live session.

Class 19 - Ensemble Learning: Introduction to ensemble learning, bagging, boosting, and stacking.

Course Instructor

Teachnook Team

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