Data-Science-and-Machine-Learning-My-self-Education

This repo has all the files that I used during the studies of ML and DS

Syllabus

Link:https://drive.google.com/file/d/1LnAzX7B8ahSXll1cpvIzUk7PuISqFml0/view

Name		Name	Last commit message	Last commit date
Latest commit History 29 Commits
Module 1 : Fundamentals of Programming		Module 1 : Fundamentals of Programming
Module 11 : Assignments		Module 11 : Assignments
Module 2: Data Science: Exploratory Data Analysis and Data Visualization		Module 2: Data Science: Exploratory Data Analysis and Data Visualization
Module 3 : Foundations of Natural Language Processing and Machine Learning		Module 3 : Foundations of Natural Language Processing and Machine Learning
Module 4 : Machine Learning- II (Supervised Learning Models)		Module 4 : Machine Learning- II (Supervised Learning Models)
Module 5 : Feature Engineering, Productionisation and deployment of ML Models		Module 5 : Feature Engineering, Productionisation and deployment of ML Models
Module 6 : Machine Learning Real-World Case Studies		Module 6 : Machine Learning Real-World Case Studies
Module 7 : Data Mining(Unsupervised Learning) and Recommender Systems + Real -world Case Studies		Module 7 : Data Mining(Unsupervised Learning) and Recommender Systems + Real -world Case Studies
Module 8 : Neutral Networks, Computer Vision and Deep Learning		Module 8 : Neutral Networks, Computer Vision and Deep Learning
Module 9: Deep Learning Real-World Case Studies		Module 9: Deep Learning Real-World Case Studies
Module10 : Misc.		Module10 : Misc.
LICENSE		LICENSE
README.md		README.md

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Module 1 : Fundamentals of Programming

Module 1 : Fundamentals of Programming

Module 11 : Assignments

Module 11 : Assignments

Module 2: Data Science: Exploratory Data Analysis and Data Visualization

Module 2: Data Science: Exploratory Data Analysis and Data Visualization

Module 3 : Foundations of Natural Language Processing and Machine Learning

Module 3 : Foundations of Natural Language Processing and Machine Learning

Module 4 : Machine Learning- II (Supervised Learning Models)

Module 4 : Machine Learning- II (Supervised Learning Models)

Module 5 : Feature Engineering, Productionisation and deployment of ML Models

Module 5 : Feature Engineering, Productionisation and deployment of ML Models

Module 6 : Machine Learning Real-World Case Studies

Module 6 : Machine Learning Real-World Case Studies

Module 7 : Data Mining(Unsupervised Learning) and Recommender Systems + Real -world Case Studies

Module 7 : Data Mining(Unsupervised Learning) and Recommender Systems + Real -world Case Studies

Module 8 : Neutral Networks, Computer Vision and Deep Learning

Module 8 : Neutral Networks, Computer Vision and Deep Learning

Module 9: Deep Learning Real-World Case Studies

Module 9: Deep Learning Real-World Case Studies

Module10 : Misc.

Module10 : Misc.

LICENSE

LICENSE

README.md

README.md

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