manju savanth's repositories
analysis
Repo for practical data science problems approaches, including notebook demo and working scripts | #DS | #analysis
coding-exercises
My implementation of useful data structures, algorithms, as well as my solutions to programming puzzles.
cracking-the-data-science-interview
A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
Data-science-best-resources
Carefully curated resource links for data science in one place
Data-Science-with-python
This repo has all the required materials of the Data science with python video series.
data_science_resources
đź“Š Data Science Resources, Data Science Standards & Machine Learning Pipelines
data_science_standards
Data Science Standards - Framework to Productionize Projects throughout the Data Science and Production Solution Lifecycle
Deep-learning-with-Python
Deep learning codes and projects using Python
deploying-machine-learning-models
Example Repo for the Udemy Course "Deployment of Machine Learning Models"
great_expectations
Always know what to expect from your data.
Machine-Learning-Deployment-Tutorials
Sample end to end projects from data collection to putting models into production using flask, docker etc.
machine-learning-systems-design
A booklet on machine learning systems design with exercises
Machine-Learning-with-Python-1
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
madewithml
Learn how to responsibly deliver value with applied ML.
medium_articles
Scripts used for articles published on Medium
MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
MLAlgorithms
Minimal and clean examples of machine learning algorithms implementations
NLP-with-Python
Scikit-Learn, NLTK, Spacy, Gensim, Textblob and more
python-deepdive
Python Deep Dive Course - Accompanying Materials
Python-Natural-Language-Processing-Cookbook
Python Natural Language Processing Cookbook, published by Packt
testing-and-monitoring-ml-deployments
Example project for the course "Testing & Monitoring Machine Learning Model Deployments"