ISLR: Introduction to Statistical Learning with Applications in R by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani, ISBN 978-1-4614-7137-0
Hands-on: Hands-On Machine Learning with Scikit-Learn & TensorFlow by Aurélien Géron, ISBN 978-1-491-96229-9
Created my first database replication server, a Postgres replication server from server to laptop following book “PostgreSQL Replication” by Hans-Jürgen Schönig and Zoltan Böszörmenyi.
Wrote an API using python, falcon, and psycopg2 for storing data from garage sensors into a postgresql database.
Build LSTM using Keras on TensorFlow for predicting the number of parking spaces available in each parking garage.
On parking garage data, added circular statistics to hour of the day and day of the year, and increased accuracy on generalized linear model by 1% from 77% to 78% using h2o Flow. Started learning the basics of TensorFlow, computational graphs, constants/variables/placeholders, sessions.
Reading Hands-on, chapters 2 (data processing, scikit-learn pipelines), 9 (intro to TensorFlow), and 14 (RNNs and LSTMs).
SpotMe, viewing and cleaning parking garage data so that it can be used to train a machine learning model. Learned about a tool called h2o.ai.
Started working for SJSU student-led startup SpotMe Solutions.
ISLR Chapter 4 Logistic Regression (page 136).
Handson-ML Chapter 2 End-to-End Machine Learning Project (page 49).
Things on my links page (https://www.violet-mica.com/links/).
https://www.deeplearning.ai/ (Deep Learning Coursera Specialization by Andrew Ng).