For Those Learning Artificial Intelligence

• The field of AI is closely related to many other research areas, making it surprisingly difficult to grasp the full picture. The following roadmap might help you understand the overall landscape.
  Conference map

• For those who want to learn more, the following slides provide a good overview. They were created by the Japanese Society for Artificial Intelligence and cover the outline and details of AI research.
  AI Research Overview for Beginners and Researchers from Other Fields

Recommendations for Learning Machine Learning

Before studying deep learning (especially neural networks), which is the current mainstream approach, we recommend first learning traditional statistical (non-deep-learning) models. These methods have relatively straightforward theory, making them ideal for beginners, and understanding them will help you appreciate why deep learning became necessary.

This website provides a good understanding of well-known models:
Series: Learning Machine Learning from Basics with Python

Learning Python + Essential Skills

Practice fundamental operations through the "100 Knocks" series.

NLP 100 Knocks

• NLP 100 Knocks 2020: https://nlp100.github.io/ja/ ← NEW!
• NLP 100 Knocks 2015: http://www.cl.ecei.tohoku.ac.jp/nlp100/ → Answers and Explanations
• Covers not only NLP but also basic UNIX operations and machine learning
• Related: Before Starting NLP 100 Knocks

Image Processing 100 Knocks

• https://github.com/yoyoyo-yo/Gasyori100knock

Deep Learning Infinite Knocks

• https://github.com/yoyoyo-yo/DeepLearningMugenKnock

NumPy 100 Knocks

• https://github.com/rougier/numpy-100/blob/master/100_Numpy_exercises.md

Pandas 100 Knocks

• https://www.kaggle.com/python10pm/pandas-100-tricks

Data Science 100 Knocks

• https://github.com/The-Japan-DataScientist-Society/100knocks-preprocess

YouTube

• Sony Neural Network Console
  • Deep Learning Introduction Playlist