shrikant-temburwar
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A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Course Files for Complete Python 3 Bootcamp Course on Udemy
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
📡 Simple and ready-to-use tutorials for TensorFlow
A repo for data science related questions and answers
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.
Portfolio of data science projects completed by me for academic, self learning, and hobby purposes.
DataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc.
Preparing for machine learning interviews
Code for the online course "Deployment of Machine Learning Models"
A content-based recommender system that recommends movies similar to the movie the user likes and analyses the sentiments of the reviews given by the user
Short Tutorial to Probabilistic Graphical Models(PGM) and pgmpy
Methods with examples for Feature Selection during Pre-processing in Machine Learning.
PyTorch Implementation of "Large-Scale Image Retrieval with Attentive Deep Local Features"
Malware Detection and Classification Using Machine Learning
Pytorch Implementation of Unifying Deep Local and Global Features for Image Search (DELG)
How to Win a Data Science Competition: Learn from Top Kagglers
State of the Art Language models and Classifier for Hindi language (spoken in Indian sub-continent)
Content based movie recommendation system with sentiment analysis
Deploying a simple machine learning model to an AWS ec2 instance using flask and docker.
This is a hollywood movie recommender system built with Python.
PyTorch implementation of DELG paper.
Basic of Recommendation Models
Recommend similar apparel items/products in ecommerce.
effective word embeddings for the hindi language
Applying Recurrent Neural Network ( RNN ) with multiple LSTM layers on a dataset which contains data collected by accelerometer and gyroscope sensors of mobile phone in order to classify the human …