normanli33's repositories
openai-cookbook
Examples and guides for using the OpenAI API
pytorch-deep-learning_youtube
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
python3-cookbook-
《Python Cookbook》 3rd Edition Translation
GradientDescentExample
Example demonstrating how gradient descent may be used to solve a linear regression problem
stat_rethinking_2023
Statistical Rethinking Course for Jan-Mar 2023
artofpostgresql
repo hold my artifacts working through the book, The Art of PostgreSQL
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
Data_Analysis_and_Prediction_Algorithms_with_R
Repository for data science book
youtube_channel
Notebooks for the python tutorials of my youtube channel. See specific youtube video for link to specifc notebook.
PythonNumericalDemos
Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.
ISLR-python
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
GeoDataSets
Synthetic datasets for geoscience (geo)statistical modeling
LaTeX-Beginner-s-Guide-Second-Edition
LaTeX Beginner's Guide - Second Edition, published by Packt
handson-ml2
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.
Doing-Bayesian-Data-Analysis-in-brms-and-the-tidyverse
The bookdown version lives here: https://bookdown.org/content/3686
algorithms-sedgewick-python
Algorithms(4th edition) by Robert Sedgewick and Kevin Wayne exercises in python
R-Tutorial-Data-Files
Contains data files that are referenced in R tutorials from the following YouTube playlist: https://www.youtube.com/playlist?list=PLKkRkURCtPjCJOZHskCoyJCPb8wMDs2CW
stat453-deep-learning-ss21
STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2021)
cheatsheets
RStudio Cheat Sheets
pandas-tutorial
This is the cheat sheet Jupyter Notebook I made for my Pandas Learn in One Video Tutorial. I basically condensed the Pandas API down into this one cheat sheet with hundreds of examples. I hope you find it useful.
531w21-Analysis-of-Time-Series
Stats 531 (Winter 2021) ‘Analysis of Time Series’ (https://ionides.github.io/531w21/)
PySpark_DataFrame_SQL_Basics
The Repository for all code I use in my Data Science and Machine Learning Tutorials on YouTube
calm-notebooks-scikit-learn-crash-course
notebooks that are used at calmcode.io https://www.youtube.com/watch?v=0B5eIE_1vpU
statsofdoom-files
Files for courses avalaible on statstools
DBDA-python
Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code
Doing_bayesian_data_analysis
Python/PyMC3 versions of the programs described in Doing bayesian data analysis by John K. Kruschke
demand-prediction-guide
2021 - Github companion to "Demand Prediction in Retail: A Practical Guide to Leverage Data and Predictive Analytics" (Springer Series in Supply Chain Management, 14)