machine learning course programming exercise. Contribute to xiaodanjiao/Stanford-Machine-Learning-Course development by creating an account on GitHub.
sohansai/machine-learning-andrew-ng Star35 This repository contains codes of Andrew Ng's course Machine learning machine-learningcourseramachinelearningmachine-learning-courseraandrew-ngstanford-machine-learningsupervised-machine-learningunsupervised-machine-learningandrew-ng-coursecoursera-specializationandrewngandre...
前言 相信经常混Machine Learning各大学习圣地的朋友们多少有听说过斯坦福大学的CS229机器学习课程(Stanford's CS 229 Machine Learning course)的呢,今天在GitHub上看到一个项目,作者Afshine Amidi (Ecole Centrale Paris, MIT)总结了自己学习该课程的重要知识点,然后每个模块输出一张囊括重点的图表(有点像我们期末备...
Machine learning definition ( Field of study that gives computers the ability to learn without being explicitly programmed. ) Machine learning algorithms: Supervised learning and unsupervised learning, reinforcement learning, recommender systems. Supervised learning (e.g., regression, classification, naive b...
CMU Machine Learning一系列课程的门槛,必选。特别是对于想要往Machine Learning发展,但是比较犹豫、对自己的能力评估得并不是特别到位的同学,上完这几门课,基本就被安排得明明白白了;如果是在Machine Learning 方面有基础的同学,这课就相当于复习巩固,也挺好。为什么说那些犹豫的同学会被安排得明明白白?是因为上了这...
数据显示:金融服务行业、科技、媒体、电信行业,对数据工程师(Data engineers)、AI数据科学(AI data scientists)和机器学习工程师(Machine learning engineers)的需求比较旺盛。 AI数据科学(AI data scientists)职业,在美国其实主要工作类似我们国内的应用数学领域,主要是AI领域数学方面的研究和应用。
I was the homework grader for the Fall 2018-2019 offering of Stanford’s Math 52 course: Integral Calculus of Several Variables. Library Assistant @ Stanford Terman Engineering Library (September 2018 - January 2019) I was a library assistant in Stanford’s Terman Engineering Library during my fa...
深度学习之course1———神经网络和深度学习 网络What is aNeuralNetwork 深度学习=训练(非常大)神经网络一个非常简单的神经网络:房屋价格大小线性回归一个更大的神经网络上图只是一个手工演示的更大的神经网络,与实际的区别: 1.隐藏层不是手工设置的2.每一层都是上一层所有输入的函数 实际的神经网络:真实神经...
The Stanford course on deep learning forcomputer visionis perhaps the most widely known course on the topic. This is not surprising given that the course has been running for four years, is presented by top academics and researchers in the field, and the course lectures and notes are ma...
The 19th-century British philosopher Thomas Carlyle ascribed human progress to a key historical development: “Man is a tool-using animal. Without tools he is nothing, with tools he is all.” While today’s large language models (LLMs) have demonstrated