[PYTHON] Record the steps to understand machine learning

You will be able to understand roughly with 3 videos and 1 book

I will write with a concept like

Recommended videos

1 hour with 3 bottles. If you look at this, it's OK

  1. Try moving first: "[Introduction to Machine Learning] Beginners first make a moving model"
  2. Understanding the touch of deep learning: "Introduction to deep learning that is so easy to understand that you do not need an internal job"
  3. Entrance to learn python library: "[Introduction to machine learning] scikit-learn [Library you want to know]"

Recommended Python books

I try to get about 5 knocks every day. You can probably go while googled, but I think that it will be the shortest distance if you know it systematically.

  1. [Try to touch anyway](https://www.amazon.co.jp/ Python practice data analysis 100 knocks-Shimoyama-Terumasa / dp / 4798058750) "Python practice data analysis 100 knocks"

What should I understand after all?

If you do the above, you will learn the following.

--Experience of writing Python, creating a model, and predicting --Be aware that you can get and try various data by going to Kaggle's site. ――A feeling of what kind of image an algorithm is --The algorithm solves the optimization problem. Sense --Somehow mechanisms and use cases such as regression and gradient boosting --Data preprocessing --One Hot Encoding, normalization, etc.

Extra edition

Box-like things to write down

-Short movie of activation function -What kind of algorithm is available -Environment for machine learning (example: AWS SageMaker) -Introduction to machine learning that can be used in the field by Google data scientists

What to understand next

--XGBoost example --Hyperparameter tuning items, kernel, etc.

Will I not have to study much anymore? Why it might

――The number of environments where machine learning is possible is increasing.

What I want to focus on in the future

--Data collection like MLOps-Processing-Efficiency and automation of flow like learning --AI for system development processes like AI Ops --IoT or device system

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