vamsikavuru Goto Github PK

feature_engine

Feature engineering package with sklearn like functionality

fes

Code and Resources for "Feature Engineering and Selection: A Practical Approach for Predictive Models" by Kuhn and Johnson

few-shot-vid2vid

flake8rules

Descriptions and examples for the rules in Flake8 (pyflakes, pycodestyle, and mccabe).

free-programming-books

:books: Freely available programming books

fuzzy-telegram

Fuzzy Telegram

ganlab

GAN Lab: An Interactive, Visual Experimentation Tool for Generative Adversarial Networks

gaussian-trnasformaion

git-demo

It's a demo

git_demo2

It's a ETL Project

gitrepo

google-cloud-python

Google Cloud Client Library for Python

gym

A toolkit for developing and comparing reinforcement learning algorithms.

haberman-cancer-survival-dataset-

The Haberman’s survival data set contains cases from a study that was conducted between 1958 and 1970 at the University of Chicago’s Billings Hospital on the survival of patients who had undergone surgery for breast cancer.

hadoop-training-projects

Projects from my Hadoop training sessions

hands-on-computer-vision-with-tensorflow-2

Hands-On Computer Vision with TensorFlow 2, published by Packt

hands-on-data-science-for-marketing

hands-on-gpu-accelerated-computer-vision-with-opencv-and-cuda

Hands-On GPU Accelerated Computer Vision with OpenCV and CUDA, published by Packt

hands-on-recommendation-systems-with-python

Hands-On Recommendation Systems with Python published by Packt

high-performance-data-processing-in-python

Talk demonstrating how to massively optimise data processing and numerical computation in Python

hive

Apache Hive

hungabunga

HungaBunga: Brute-Force all sklearn models with all parameters using .fit .predict!

hyperopt-sklearn

Hyper-parameter optimization for sklearn

hyperparameter-optimization

image-projection-with-opencv

With the combination of static (background) and dynamic (foreground) frames, an illusion effect is created.

insurence_fraud_detection

interpreting-machine-learning-models

Interpreting Machine learning Models(ML Models,DL models) with Lime,Eli5,Shap,etc

introtodeeplearning_labs

Lab Materials for MIT 6.S191: Introduction to Deep Learning

ipyparallel

Interactive Parallel Computing in Python

jenkins_project