Year 4, Q2 Machine Learning on kaggle

During Q1 one of the topics have been to learn about Artificial Intelligence, and after reading and listen several podcasts, I have decided that I would like to learn about Machine learning using Kaggle environment: python, jupyter notebooks, examples, a large community, competitions….

I have already completed the python course to refresh my knowledge and start this quarter on it.

The plan

So the V2MOM for this quarter will be:

• Vision: Learn about Machine Learning on Kaggle.
• Values: have fun, change habits day by day.
• Method: do courses, advance in the novice roadmap, participate on a competition, write code, read code…
• Obstacles:
  • Time.
  • Ariel’s surgery.
• Measures:
  • Do at least 3 courses.
  • Listen at least 13 hours of podcasts related to Machine Learning.
  • Compete at least in one competition.

Death line = 30/June/2021

The results (July 2021)

• Measures (Actual / target):
  • Course = python.
  • Course = Intro to Machine Learning.
  • Course = Data visualization.
  • From DotCSV channel: Aprende que son las redes neuronales (11 videos).
  • Podcast “Software 2.0“: 4 hours.
  • One notebook related to Sevilla Tourism.
  • About basis of Machine Learning: https://www.cienciadedatos.net/
  • How to solve Time Series problems with Machine Learning.
  • One notebook looking for correlation between DIX, GEX and S&P 500.
  • One notebook looking for correlation between market breadth data and S&P 500 (using a neural network).
  • One notebook looking for correlation between market breadth data and S&P 500 (using GXBoost model).
  • Machine Learning, using LSTM to predict S&P 500.
  • I have learned some concepts reading kaggle code and posts: https://joapen.com/blog/2021/04/26/learning-while-reading-kaggle-posts/
  • I have started a Work breakdown structure (WBS) document to figure out a lot of details that I have to take into account during a standard project (considering a lot of opened assumptions).
  • Notes about convolutional neural networks.
  • What is Machine Learning Operations.

Videos:

• Sequencial model with Keras: https://www.youtube.com/watch?v=EvGS3VAsG4Y
• Que es una red LSTM: https://www.youtube.com/watch?v=1BubAvTVBYs
• LSTM networks explained: https://www.youtube.com/watch?v=QciIcRxJvsM

I’m very happy this quarter with the knowledge gained on machine learning and I’m going to continue next quarter on this topic as there are so many things to be learnt.