Artificial Intelligence and Algorithm Learning (November Monthly)

Artificial Intelligence and Algorithm Learning (November Monthly)

Lonely Whistler
Bandari - Mistyland

Today, a monthly magazine is published, and the articles for nearly a month are organized for everyone, so that everyone can learn and review.

Python

1. 34 best and easy to use Python open source frameworks

Machine learning

1. Where can I find machine learning practice data? Two lines of code!

2. Summary of core knowledge points of machine learning and deep learning

3. The professor opens a lecture-what exactly is machine learning?

4. Wu Enda's suggestions on machine learning career and reading papers

Deep learning

1. [Overview] A review of deep learning suitable for novices

2. PPT Download | Li Hongyi: To understand deep learning in one day, I summarized 300 pages of PPT

3. Graph neural network is on fire? Talk about its universality and limitations

4. MLK | One article to clarify deep learning recurrent neural networks

5. Deep learning has been successfully applied in these three areas

Computer vision

1. Actual Combat | Faster RCNN of Source Code Introduction

2. A must-read article for beginners in deep learning face recognition and verification

3. 8 common bugs in computer vision deep learning

4. 100 questions image processing beginners should learn-have you learned them all?

5. Introduction to computer vision: basic concepts, operating principles, detailed application cases

Natural language processing

1. [Experience] Some tips for first entering the NLP field

2. Interview questions related to NLP algorithm engineers

3. NLP learning roadmap (mind map), very comprehensive and clear!

Reinforcement learning

1. In-depth interpretation of 8,000-word long texts, the application and latest progress of transfer learning in reinforcement learning

TensorFlow

1. TensorFlow 2.0 model: recurrent neural network

2. TF downloads have exceeded 46 million! The first TensorFlow World conference, Google Daniel Jeff Dean's passionate speech

The road of algorithm engineer

1. 2021 school recruitment algorithm post, persuade to leave or continue

2. Why should algorithm engineers contribute code to the community?

3. How do you think that the number of applicants for the 2020 school recruitment algorithm engineer position far exceeds the number of recruited positions?

4. After the age of 35, where have all the IT Internet practitioners gone?

5. For technical jobs, is it a development job or an algorithm job?

6. The core competitiveness of algorithm engineers
   

"Nezhatou"-playing with small trends