Study Progress

Abbreviations:
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

2018-08-08
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.

2018-06-27
Wrote an API using python, falcon, and psycopg2 for storing data from garage sensors into a postgresql database.

2018-06-26T
Build LSTM using Keras on TensorFlow for predicting the number of parking spaces available in each parking garage.

2018-06-24U
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).

2018-06-19T
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.

2018-06-13W
Started working for SJSU student-led startup SpotMe Solutions.

2018-06-12T
ISLR Chapter 4 Logistic Regression (page 136).
Handson-ML Chapter 2 End-to-End Machine Learning Project (page 49).

Potential resources:
Things on my links page (https://www.violet-mica.com/links/).
https://www.deeplearning.ai/ (Deep Learning Coursera Specialization by Andrew Ng).

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