ashishtele
Data Science Lead & ML Expert at Cardinal Health, UConn School of Business Alum
Cardinal HealthStamford
Pinned Repositories
66DaysofData
#66DaysOfData
ashishtele
Special Repository
ashishtele.github.io
🔥 A website showcasing my work
Kaggle-Work-EDA-Kernel
This repository contains my EDA scripts of Kaggle & MakeoverMonday Datasets
McKinsey-Hackathon
McKinsey Hackathon - Ranked 228th (top 5%)
MetaFlow_MLOps
End to end example of Metaflow and Prefect pipelines (Python)
MLOps
End to End toy example of MLOps
Power_BI
Power BI dashboards - Hackathon file, the trend of millennials and many more
Python_Scripts
Useful class scripts such as Twitter comment scrap, Facebook data map
Quick-Notes-for-ML-DS
It contains interview preparation notes provided by iNeuron, important links, MLOps resources
ashishtele's Repositories
ashishtele/awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
ashishtele/Survival_Analysis
Survival analysis is generally defined as a set of methods for analyzing data where the outcome variable is the time until the occurrence of an event of interest.
ashishtele/Classification_Projects
Competition Scripts: Drivendata.org
ashishtele/deep-learning-with-r-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
ashishtele/Kaggle---Kiva-Analysis
Kaggle Competition - Kiva data exploration and exploratory data analysis
ashishtele/Kaggle-Bike-Sharing-Demand
Forecast use of a city bikeshare system
ashishtele/Linear-regression---Real-estate
House sale price prediction - Ames Housing (caret), Boston house sale price etc.
ashishtele/Logistic-Regression
Salary division classification ($50k)
ashishtele/Machine-Learning-with-R-datasets
Formatted datasets for Machine Learning With R by Brett Lantz
ashishtele/Market-Basket-Analysis
UCI repository - Online Retail
ashishtele/neural-networks-and-deep-learning
Code samples for my book "Neural Networks and Deep Learning"
ashishtele/New-York-Price-Prediction---Actual-Data
Predictive Class Final project - Actual data of Brooklyn; Feature Engineering; Transformations; Model feedback using Cook's distance; Model development and comparison
ashishtele/Novelty-watches---R
Probabilistic comparison in R
ashishtele/Spotify-s-Worldwide-Daily-Song-Ranking
The 200 daily most streamed songs in 53 countries. Music streaming is ubiquitous. Currently, Spotify plays an important part on that. This dataset enable us to explore how artists and songs' popularity varies in time.
ashishtele/2015
Public material for CS109
ashishtele/DataScienceR
a curated list of R tutorials for Data Science, NLP and Machine Learning
ashishtele/dataviz
A book covering the fundamentals of data visualization.
ashishtele/deepLearningBook-Notes
Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)
ashishtele/keras
Deep Learning for humans
ashishtele/msds501
Course notes for MSAN501, computational boot camp, at the University of San Francisco
ashishtele/NoteBooks-Statistics-and-MachineLearning
http://unsupervised-learning.com
ashishtele/sas-npp
SAS language definitions for Notepad++ (UDL format)
ashishtele/stats337
Readings in applied data science