Pinned Repositories
1806
18.06 course at MIT
2021-CS109A
2021-CS109B
Algorithmic-Machine-Learning
Public course material
amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Apache-Spark-in-7-Days
Apache Spark in 7 Days [Video], by Packt Publishing
assignments
bigdata-2018f
CS 451/651 Data-Intensive Distribute Computing (Fall 2018) at the University of Waterloo
bigdata_lab
CLOUDS-LAB
Laboratory Material for the course on Cloud Computing
justinjiajia's Repositories
justinjiajia/2021-CS109A
justinjiajia/2021-CS109B
justinjiajia/eigenfaces
Using PCA and Autoencoder to extract effective features from face images. Comparison of the two on Yale Face Database B.
justinjiajia/ml-coursera-python-assignments
Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.
justinjiajia/Deep-Learning-Specialization
Coursera's Deep Learning Specialization offered by deeplearning.ai.
justinjiajia/Scalable-Machine-Learning-on-Big-Data-using-Apache-Spark
Machine learning using Pyspark
justinjiajia/assignments
justinjiajia/Interactive-Dashboards-and-Data-Apps-with-Plotly-and-Dash
Interactive Dashboards and Data Apps with Plotly and Dash, published by Packt
justinjiajia/xuhappy.github.io
justinjiajia/hw3_public
justinjiajia/interpretable-ml-class.github.io
A course on interpretability and explainability in machine learning
justinjiajia/cs182sp21.github.io
justinjiajia/winutils-1
winutils.exe hadoop.dll and hdfs.dll binaries for hadoop windows
justinjiajia/dj4e-samples
Django For Everybody Sample Code
justinjiajia/tensorflow-3-public
Public facing repo for TensorFlow Advanced Techniques specialization
justinjiajia/Scalable_Machine_Learning_on_Big_Data_using_Apache_Spark
Scalable Machine Learning on Big Data using Apache Spark
justinjiajia/InterpretableMachineLearning2020
Lecture notes for 'Interpretable Machine Learning' at WUT and UoW. Summer semester 2019/2020
justinjiajia/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.
justinjiajia/colah.github.io
justinjiajia/handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
justinjiajia/stanford-cs-230-deep-learning
VIP cheatsheets for Stanford's CS 230 Deep Learning
justinjiajia/stanford-cs-221-artificial-intelligence
VIP cheatsheets for Stanford's CS 221 Artificial Intelligence
justinjiajia/stanford-cs-229-machine-learning
VIP cheatsheets for Stanford's CS 229 Machine Learning
justinjiajia/stanford-cme-102-ordinary-differential-equations
VIP cheatsheets for Stanford's CME 102 Ordinary Differential Equations for Engineers
justinjiajia/stanford-cme-106-probability-and-statistics
VIP cheatsheets for Stanford's CME 106 Probability and Statistics for Engineers
justinjiajia/python-scraping
Code samples from the book Web Scraping with Python http://shop.oreilly.com/product/0636920034391.do
justinjiajia/cv
My CV built using RMarkdown and the pagedown package.
justinjiajia/cs228-material
Teaching materials for the probabilistic graphical models and deep learning classes at Stanford
justinjiajia/notes
CME211 Notes | Outline ->
justinjiajia/1806
18.06 course at MIT