Shuvayan Das's repositories
Agile_Data_Code
Chapter-wise code for Agile Data the O'Reilly book
analytics
Analysis of the municipal data for real time alerts, predictive analytics and more...
awesome-machine-learning-interpretability
A curated list of awesome machine learning interpretability resources.
bayesian_mmm
Code for the article Modeling Marketing Mix using PyMC3
BayesianMMM
(ml) - python implementation of bayesian media mix modelling with shape and carryover effect
burro
Exploring data together using shiny (burro(w) into the data)
change-tutorial
Materials for the useR2017 tutorial on changepoint detection
cnn-text-classification-tf
Convolutional Neural Network for Text Classification in Tensorflow
Data-Science--Cheat-Sheet
Cheat Sheets
DBDA-python
Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC code
deep-learning-book
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
deep-text-corrector
Deep learning models trained to correct input errors in short, message-like text
DeepSpell
a Deep Learning based Speller
DigitRecognizer
Kaggle Digit Recognizer
EloquentJavascript
Exercises from the book.My first foray into front end development.
Machine-Learning-Book-Collections
Feature Books for Machine Learning
mamimo
A package to compute a marketing mix model.
MMM_POSTS
MMM Solutioning Approaches
practicalAI
📚 A practical approach to learning and using machine learning.
pyculiarity
A Python port of Twitter's AnomalyDetection R Package
pydaal-tutorials
Tutorials for uisng PyDAAL, i.e. the Python API of Intel Data Analytics Acceleration Library
QueryBot_COVID19
A query bot of clinical data
reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
shinyEDA
Workshop on exploratory data analysis (EDA) using a shiny Dashboard
Stock-Market-Price-Prediction
Analysis of various deep learning based models for financial time series data using convolutions, recurrent neural networks (lstm), dilated convolutions and residual learning
time-series-forecasting-pytorch
Acquiring data from Alpha Vantage and predicting stock prices with PyTorch's LSTM
TMRMR
Minimum redundancy maximum relevance feature selection approach for temporal gene expression data.