dkryadav

100DaysOfMLCode

This repository contains all the required resources regarding the 100+ Days Of ML Code Telgram Group which was driven by me from 1-1-2019 to 31-12-2019 !!

amazon-sagemaker-from-idea-to-production

DEMO

approachingalmost

Approaching (Almost) Any Machine Learning Problem

BackOrder

Caffe_Product_Price_Estimation

In this machine learning pricing project, I implement a caffe product price optimization algorithm using regression trees

cml

♾️ CML - Continuous Machine Learning | CI/CD for ML

CreditDefaulter

To Predict Credit Card Defaulters

DataScienceInterview30DayChallenge

This is list off 30 days of interview question and answer

DATASET

python-machine-learning-by-sebastian-raschka-and-vahid-mirjalili-pdf-3rd-edition

dkryadav/python-machine-learning-by-sebastian-raschka-and-vahid-mirjalili-pdf-3rd-edition

dkryadav/DataScienceInterview30DayChallenge

This is list off 30 days of interview question and answer

dkryadav/100DaysOfMLCode

This repository contains all the required resources regarding the 100+ Days Of ML Code Telgram Group which was driven by me from 1-1-2019 to 31-12-2019 !!

dkryadav/amazon-sagemaker-from-idea-to-production

DEMO

dkryadav/approachingalmost

Approaching (Almost) Any Machine Learning Problem

dkryadav/BackOrder

dkryadav/Caffe_Product_Price_Estimation

In this machine learning pricing project, I implement a caffe product price optimization algorithm using regression trees

dkryadav/cml

♾️ CML - Continuous Machine Learning | CI/CD for ML

dkryadav/CreditDefaulter

To Predict Credit Card Defaulters

dkryadav/DATASET

dkryadav/FASTAI

dkryadav/FASTAII

dkryadav/Flask

dkryadav/HackerRank30day

dkryadav/Kaggle

Code Competition

dkryadav/LiniearRegression

In statistics, linear regression is a linear approach to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables). The case of one explanatory variable is called simple linear regression

dkryadav/MLBOOKSCOLLECTION

dkryadav/MLDS100BOOK

dkryadav/MLE-Questions

dkryadav/pandas-videos

Jupyter notebook and datasets from the pandas Q&A video series

dkryadav/Papers-Literature-ML-DL-RL-AI

Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning

dkryadav/Practical_MachineLearning_Coursera

dkryadav/ReccomendorSystem

dkryadav/RecommendorSysMovie

dkryadav/Resume-Parser

Names of organizations they have worked in and the years they were working in them. Certain resumes might not have this information, so you can ignore them. 2. Names of institutions and colleges they have studied in and the associated years.

dkryadav/scikit-learn

scikit-learn: machine learning in Python

dkryadav/SPRINGER-BOOKS

FREE SPRINGER DATA SCIENCE STATISTIC BOOKS

dkryadav/Tenserflow_Coursera

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

dkryadav/TimeSeriesDatetime

dkryadav/Wafer

Fault Detection in wafer