Item: Machine Learning
Rating: 5
Author: Pradyumn Singh

Machine Learning

Machine Learning Introduction
- Machine Learning Introduction
Machine Learning Algorithms
- Machine Learning Algorithms
Supervised Learning
- Supervised Learning
Linear Regression and Logistic Regression
- Linear Regression and Logistic Regression
K-Nearest Neighbour (KNN)
- K-Nearest Neighbour (KNN)
Decision Tree
- Decision Tree
Nau00efve Bayes Classifier
- Naïve Bayes Classifier
Unsupervised Learning
- Unsupervised Learning
Advanced Machine Learning Concepts
- Advanced Machine Learning Concepts
Random Forest u2013 Ensemble
- Random Forest – Ensemble
Support Vector Machine (SVM)
- Support Vector Machine (SVM)
Natural Language Processing (NLP)
- Natural Language Processing (NLP)
Artificial Neural Network (ANN)
- Artificial Neural Network (ANN)
Tensorflow overview and Deep Learning Intro
- Tensorflow overview and Deep Learning Intro

We, at Techstack academy believe in providing our students with the real, and lifetime projects to work on. This helps to check the best of their abilities, thereby letting them know the ways of self evaluating themselves on the basis of how far they have come along with the course. To maintain the formula that there are different test-metrics and trackers included within these, we will let you know about it all, beginning from the start until you become a master/pro in it. Implement the easiest test cases and scenarios to become successful within the practicality of the process.

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