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Name: YICHUN TSAI
Type: User
Company: State Farm Insurance
Bio: I am working as a lead data scientist in State Farm Insurance. I am learning ML and Deep Learning and this document my projects.
Location: Bloomington IL
Name: YICHUN TSAI
Type: User
Company: State Farm Insurance
Bio: I am working as a lead data scientist in State Farm Insurance. I am learning ML and Deep Learning and this document my projects.
Location: Bloomington IL
📢 Ready to learn or review your knowledge! You will learn 10 skills as data scientist: 📚 Python, Machine Learning, Deep Learning, Data Cleaning, EDA, python packages such as Numpy, Pandas, Seaborn, Matplotlib, Plotly, Tensorfolw, Theano...., Linear Algebra, Big Data, Analysis Tools and solve some real problems such as predict house prices.
A python library to scrape data from amazon.com
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
SageMaker Course Material
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
Personal notes for SAA-C02 test from: https://learn.cantrill.io
Mapping a variable-length sentence to a fixed-length vector using BERT model
Building your first LLM application with OpenAI, Chainlit, and Hugging Face, step-by-step!
Uplift modeling and causal inference with machine learning algorithms
I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!
Interactive deep learning book with code, math, and discussions. Available in multi-frameworks. Adopted at 140 universities.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Repository for last project in Data Science Specialization by John Hopkins University
The Leek group guide to data sharing
Deep Learning Specialization by Andrew Ng on Coursera.
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
Contains files related to content and project of DSND
Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras
Example deep learning projects that use wandb's features.
Draft of the fastai book
A functional, Data Science focused introduction to Python
18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Gradient boosting model for predicting credit default risk on Kaggle competition
Image classifier using Pytorch
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.