patelke's repositories
30-Days-Of-Python
30 days of Python programming challenge is a step by step guide to learn Python programming language in 30 days.
Data-Science--Cheat-Sheet
Cheat Sheets
dlbook_exercises
Exercises for the Deep Learning textbook at www.deeplearningbook.org
learn-python
📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.
modeldrift
Capturing model drift and handling its response - Example webinar
Predicting-Consumer-Conversion
Direct Marketing Optimization - Ensemble Methods
Python-Coding
Sorting, sentiment analysis, dijkstra
Text-Classification-and-Topic-Modelling
Predicting Traffic Complaints in Boston with Text Mining
awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
conjugate_prior
Implementation of the conjugate prior table for Bayesian Statistics
data-science
:bar_chart: Path to a free self-taught education in Data Science!
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
learn-python3
Jupyter notebooks for teaching/learning Python 3
lux
Python API for Intelligent Visual Data Discovery
machine-learning-systems-design
A booklet on machine learning systems design with exercises
Medium_Blogs_Analytics
Understanding the factors impacting number of claps on medium blogs - medium.com
NLP-research-papers
This repository contains landmark research papers in Natural Language Processing that came out in this century.
numpy
The fundamental package for scientific computing with Python.
pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Python
All Algorithms implemented in Python
text-analytics-with-python
Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.
theMLbook
The Python code to reproduce the illustrations from The Hundred-Page Machine Learning Book.
twitter-sentiment-analysis
Sentiment analysis of a tweet/series of tweets using libraries 'tweepy' and 'textblob'