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/amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
justinjiajia/Apache-Spark-in-7-Days
Apache Spark in 7 Days [Video], by Packt Publishing
justinjiajia/bigdata_lab
justinjiajia/coursera-deep-learning-specialization
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
justinjiajia/cs182sp22.github.io
justinjiajia/cs224u
Code for Stanford CS224u
justinjiajia/Dash-by-Plotly
Interactive data analytics
justinjiajia/datafiles
justinjiajia/deep-learning-pytorch-huggingface
justinjiajia/deeplearning
justinjiajia/Generative-AI-with-LLMs
In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.
justinjiajia/img
justinjiajia/intro-workshop
Associated files for the an introductory Weaviate online workshop
justinjiajia/introtodeeplearning
Lab Materials for MIT 6.S191: Introduction to Deep Learning
justinjiajia/loss-landscape
Code for visualizing the loss landscape of neural nets
justinjiajia/machine_learning_refined
Notes, examples, and Python demos for the 2nd edition of the textbook "Machine Learning Refined" (published by Cambridge University Press).
justinjiajia/Made-With-ML
Learn how to responsibly deliver value with ML.
justinjiajia/ml
justinjiajia/ml-with-apache-spark
A series of Jupyter notebooks that walk you through Machine Learning with Apache Spark ecosystem using Spark MLlib, PyTorch and TensorFlow.
justinjiajia/multimodal-workshop
justinjiajia/ng-video-lecture
justinjiajia/openai-cookbook
Examples and guides for using the OpenAI API
justinjiajia/scaling-machine-learning-course
Scaling Machine Learning in Three Week course in a collaboration with O'Reilly following the guidance of Adi Polak's book - Scaling Machine Learning with Spark
justinjiajia/spark-nlp-workshop
Public runnable examples of using John Snow Labs' NLP for Apache Spark.
justinjiajia/technical-documents
Technical documents on a variety of topics, created for the purpose of learning
justinjiajia/tensorflow-1-public
justinjiajia/tensorflow-2-public
justinjiajia/Understanding-Deep-Learning-Book
Understanding Deep Learning - Simon J.D. Prince