ashishtele
Data Science Lead & ML Expert (Functional Manager) at Cardinal Health, Data Science graduate from UConn School of Business
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/Quick-Notes-for-ML-DS
It contains interview preparation notes provided by iNeuron, important links, MLOps resources
ashishtele/MetaFlow_MLOps
End to end example of Metaflow and Prefect pipelines (Python)
ashishtele/MLOps
End to End toy example of MLOps
ashishtele/Power_BI
Power BI dashboards - Hackathon file, the trend of millennials and many more
ashishtele/ashishtele.github.io
🔥 A website showcasing my work
ashishtele/Python_Scripts
Useful class scripts such as Twitter comment scrap, Facebook data map
ashishtele/66DaysofData
#66DaysOfData
ashishtele/ashishtele
Special Repository
ashishtele/Deep_Learning_Class_Jeff
Scripts from Deep Learning class
ashishtele/Kaggle-Work-EDA-Kernel
This repository contains my EDA scripts of Kaggle & MakeoverMonday Datasets
ashishtele/McKinsey-Hackathon
McKinsey Hackathon - Ranked 228th (top 5%)
ashishtele/Tableau
A repository of Tableau dashboards: Academic projects, MakeoverMonday, Capstone
ashishtele/100-Days-Of-ML-Code
100 Days of ML Coding
ashishtele/deck.gl-data
Data for the data visualization library deck.gl examples (https://uber.github.io/deck.gl/#/)
ashishtele/DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
ashishtele/ds-optimus
How to do data science with Optimus, Spark and Python.
ashishtele/fastbook
Draft of the fastai book
ashishtele/industry-machine-learning
A curated list of applied machine learning and data science notebooks and libraries across different industries.
ashishtele/Machine_Learning_hands_on_projects
Implementing Machine learning algorithms on available datasets
ashishtele/Python-Visualization
It contains my practice scripts for Python Visualization
ashishtele/PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
ashishtele/Text_Mining
My scripts on text mining
ashishtele/Time-Series
It contains my scripts for the times series analysis
ashishtele/Travelers-Fraud-Detection-Kaggle-Competition
Invite only Kaggle Predictive Modeling Competition
ashishtele/awesome-R
A curated list of awesome R packages, frameworks and software.
ashishtele/hugging-face-LM
This repository is to test the language model from HuggingFace
ashishtele/mli-resources
H2O.ai Machine Learning Interpretability Resources
ashishtele/practical-machine-learning-with-python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
ashishtele/full-stack-fastapi-template
Full stack, modern web application template. Using FastAPI, React, SQLModel, PostgreSQL, Docker, GitHub Actions, automatic HTTPS and more.
ashishtele/Try-Your-Luck
Fill the data for Shop and Stop promotion