saisatish09's repositories
Hands-On-Natural-Language-Processing-with-Pytorch
Hands-On Natural Language Processing with Pytorch [Video], by Packt Publishing
feature-engineering-for-machine-learning
Code Repository for the online course Feature Engineering for Machine Learning
course-v3
The 3rd edition of course.fast.ai
saisatish
My First Github Page
lifelines
Survival analysis in Python
Simple-CNN-on-MNIST
Simple Tutorial on applying CNN on MNIST dataset
The-Complete-Neural-Networks-Bootcamp-Theory-Applications
Code Files for the Udemy Course: The Complete Neural Networks Bootcamp: Theory, Applications
PE-pricing-analytics
Half day workshop covering insurance pricing with GAMs, GLMs, trees and clustering.
StudyBook
Study E-Book(ComputerVision DeepLearning MachineLearning Math NLP Python ReinforcementLearning)
ANLP
Applied Natural Language Processing course code(s)
nlp_workshop_odsc19
Contains all tutorials and hands-on examples for the ODSC 2019 Workshop
course-nlp
A Code-First Introduction to NLP course
data_science_for_all
Code and resources for my blog and articles to share Data Science and AI knowledge and learnings with everyone
numerical-linear-algebra
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
anaconda-1
Graphical system installer
TensorFlow-Tutorials
TensorFlow Tutorials with YouTube Videos
Regression
This application constitutes a didactic modeling process. The user can try to perform a linear regression model based on the ordinary least squares method step by step. The application addresses a safety problem in the rural areas of Antioquia - Colombia. Through variables related to education, sport and safety itself, we seek to obtain a statistically valid model with a good adjusted R squared.
xgboost-virtual-data-science-seminar
XGBoost Insurance Pricing code comparing results with GLM and GAM for Actuarial Virtual Data Science Seminar
python-deepdive
Python Deep Dive Course - Accompanying Materials
courses
fast.ai Courses
nlp_workshop_dhs18
Contains code and presentation for our full day workshop, 'Getting Started with Natural Language Processing'. This is created for the purpose of being presented in Analytics Vidhya's DataHack Summit 2018. Authors: Dipanjan Sarkar & Raghav Bali
feature_engineering_session_dhs18
Contains code and presentation for my interactive hack session, 'Effective Feature Engineering: A Structured Approach to Building Better Machine Learning Models' where we look at two interesting case studies on how to effectively leverage feature engineering and use a structured approach to build good machine learning models. This is created for the purpose of being presented in Analytics Vidhya's DataHack Summit 2018
pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media