Pinned Repositories
awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
awesome-python-applications
💿 Free software that works great, and also happens to be open-source Python.
bayesian_first_aid
Inside every classical test there is a Bayesian model trying to get out.
bayesianprobabilitiesworkshop
A collection of questions and solutions to problems presented at Rasmus Bååth's Bayesian probabilities workshop.
Bert_with_keras_custom_layer
cracking-the-data-science-interview
Resources for Oreilly's "Cracking the Data Science Interview" video series.
data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
data-science-primer
A set of self paced resources for anyone looking to get into data science. The materials assume an absolute beginner and are intended to prepare students for the Galvanize Data Science interview process: http://www.galvanize.com/courses/data-science/
DeepLearningWithTF2.0
Practical Exercises in Tensorflow 2.0 for Ian Goodfellows Deep Learning Book
HackerRank_solutions
317 efficient solutions to HackerRank problems
vidhyarthib's Repositories
vidhyarthib/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
vidhyarthib/Python-1
All Algorithms implemented in Python
vidhyarthib/awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
vidhyarthib/awesome-python-applications
💿 Free software that works great, and also happens to be open-source Python.
vidhyarthib/murmur
A mailing list designed to reduce noise and encourage sharing
vidhyarthib/wikum
tool for collectively summarizing large discussions
vidhyarthib/wtfpython
If you think you know Python, think once more!
vidhyarthib/python
Basic intro to python
vidhyarthib/HackerRank_solutions
317 efficient solutions to HackerRank problems
vidhyarthib/personal_data_science_projects
vidhyarthib/Learn_ML_in_6_Months
Become a good Machine Learning Engineer
vidhyarthib/DeepLearningWithTF2.0
Practical Exercises in Tensorflow 2.0 for Ian Goodfellows Deep Learning Book
vidhyarthib/leetcode
The mediocre solutions to leetcode problems using Python
vidhyarthib/SurvivalAnalysis
Example fitting KM and CPH to telco churn dataset
vidhyarthib/spotify-data
Full-stack data project
vidhyarthib/mysal
My Somewhat Awesome List
vidhyarthib/nlp
Code written as a part of assignments for CSE556 Natural Language Processing taught by Dr. Tanmoy Chakraborty at IIIT Delhi in Monsoon 2018
vidhyarthib/Bert_with_keras_custom_layer
vidhyarthib/theory-statistical-modelling
This repository contains all the notes i've written in learning to become a Data Scientist, the notebooks contain specifically the theoretical implementations of Machine Learning algorithms, Deep Learning algorithms, Linear & Non-Linear Method for statistical modelling.
vidhyarthib/spotifyMe
spotifyMe is a thin client library for collecting spotify data into a Pandas Dataframe using Spotify Web API
vidhyarthib/cracking-the-data-science-interview
Resources for Oreilly's "Cracking the Data Science Interview" video series.
vidhyarthib/machine_learning_examples
A collection of machine learning examples and tutorials.
vidhyarthib/data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
vidhyarthib/Machine-Learning-Tutorials
machine learning and deep learning tutorials, articles and other resources
vidhyarthib/data-science-primer
A set of self paced resources for anyone looking to get into data science. The materials assume an absolute beginner and are intended to prepare students for the Galvanize Data Science interview process: http://www.galvanize.com/courses/data-science/
vidhyarthib/bayesianprobabilitiesworkshop
A collection of questions and solutions to problems presented at Rasmus Bååth's Bayesian probabilities workshop.
vidhyarthib/bayesian_first_aid
Inside every classical test there is a Bayesian model trying to get out.
vidhyarthib/LaplacesDemon
A complete environment for Bayesian inference within R
vidhyarthib/vaderSentiment
VADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.