MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP graduate students, university professors, and researchers in enterprises. The vision of the community is to promote communication and progress among the academic and industrial circles of natural language processing and machine learning, especially for beginners. Reprinted from … Read more
Source | Asynchronous | Book Giveaway at the End 01 How to Build the Simplest GPT What is the Learning Method for GPT? Borrowing the famous quote from Linus, “talk is cheap, show me the code”, there is nothing more suitable than building a GPT from scratch. Some students may be intimidated, thinking that something … Read more
Original link:https://medium.com/towards-artificial-intelligence/one-lego-at-a-time-explaining-the-math-of-how-neural-networks-learn-with-implementation-from-scratch-39144a1cf80 From:Yongyu Excerpted from Algorithm Notes https://github.com/omar-florez/scratch_mlp/ The author explains step by step the mathematical processes used in training a neural network from scratch. Neural networks are cleverly arranged linear and nonlinear modules. The above image describes some of the mathematical processes involved in training a neural network. We will explain this in the … Read more
This series of tutorials serves as notes for the book “Hands-On Machine Learning.” First, let’s discuss the reasons for writing this series: First, the code in “Hands-On Machine Learning” is written in Python 2, and some of the code will throw errors when run on Python 3. This tutorial revises the code based on Python … Read more
A crucial step in training a chatbot is word vector training. Whether it’s a generative chatbot or a retrieval-based chatbot, it is necessary to convert text into word vectors. The most popular word vector training model nowadays is Word2Vec. Today, I will guide you through training word vectors using Chinese Wikipedia. Training Data Download We … Read more
Produced by Big Data Digest Author: Jiang Baoshang Many students, after starting with machine learning, directly use TensorFlow to implement neural networks, with little understanding of the underlying mechanisms of neural networks. Programming languages and frameworks evolve rapidly, so understanding the principles behind them is essential. Below, we will implement a neural network step by … Read more
Author: Guo Bi Yang This article mainly summarizes the computational and programming problems from cs224n’s assignment 2. I found this assignment design to be excellent, progressing step by step, with both theory and practice, and a moderate level of difficulty. The overall structure feels more like a detailed tutorial. Therefore, I will review and reflect … Read more
Python Data Science & Machine Learning: These Optimization Tips You Probably Don’t Know! Introduction Dear Python developers and data science enthusiasts, have you ever encountered the following scenarios: Spent several days doing data analysis with Python, but the program runs slowly, and memory consumption is through the roof? Trying to tune a deep learning model … Read more
Machine Heart Report Contributor: Siyuan With the popularity of frameworks like TensorFlow and PyTorch, building neural networks often just involves calling a few API lines. Most developers have become unfamiliar with the underlying mechanisms, especially how to implement neural networks using pure NumPy. Previously, Machine Heart introduced how to implement a simple convolutional neural network … Read more
Produced by Big Data Digest Source: eisenjulian Compiled by: Zhou Jiale, Qian Tianpei Using deep learning libraries like TensorFlow and PyTorch to write a neural network is no longer a novelty. But do you know how to elegantly build a neural network using Python and NumPy? Nowadays, there are many deep learning frameworks available, equipped … Read more