Python Machine Learning ProjectsAlexander T. Combs
Lesson 32: Google Colab for Machine Learning Projects Lesson 33: Using Kaggle in Machine Learning Projects Appendix Appendix A: Python Books Appendix B: How to Set up a Workstation for Python Appendix C: Small Tricks You can see that each part targets a specific learning outcome, and so does...
https://github.com/WillKoehrsen/machine-learning-project-walkthrough 问题定义 编码之前的第一步是了解我们试图解决的问题和可用的数据。在这个项目中,我们将使用公共可用的纽约市的建筑能源数据【1】。 目标是使用能源数据建立一个模型,来预测建筑物的Energy Star Score(能源之星分数),并解释结果以找出影响评分的...
Making Developers Awesome at Machine Learning Click to Take the FREE Python Machine Learning Crash-Course Get Started Blog Topics Attention Better Deep Learning Calculus ChatGPT Code AlgorithmsImplementing machine learning algorithms from scratch. Computer Vision Data Preparation Deep Learning (keras)Deep...
We update the top AI and Machine Learning projects in Python. Tensorflow has moved to the first place with triple-digit growth in contributors. Scikit-learn dropped to 2nd place, but still has a very large base of contributors.
作者:Peter 红色石头的个人网站: 红色石头的个人博客-机器学习、深度学习之路 系列文章: 吴恩达《Machine Learning》精炼笔记 1:监督学习与非监督学习 吴恩达《Machine Learning》精炼笔记 2:梯度下降与正规…
Machine Learning Toolkit Get to know how to choose the right tools like PyTorch and TensorFlow for your Machine Learning projects. This section offers insights on industry-standard tools. #22 Course Python Deep Learning: PyTorch vs Tensorflow ...
MOOC : machine learning 和Data Analyst Nanodegree 这里是一些Blog. 机器学习理论 The Elements of statistical Learning Introduction to Statistical Learning 书: Introduction to machine learning A Course in Machine Learning. 还有一些 Watch 15 hours theory of machine learning! 越看越懒得翻,着实没什么营养...
常见的机器学习有三种:无监督学习(Unsupervised learning,分类与回归),监督学习(Supervised learning,聚类),强化学习(Reinforcement learning,与动态环境交互)。 2 核心 对数据进行泛化,就是机器学习的核心,而泛化过程中可能出现两种错误:欠拟合和过拟合。 其中,欠拟合相对简单,因为我们很容易可以从数据拟合效果中看出是否...
Hands-On Python Machine Learning with Real World Projects创建者 Sayman Creative InstituteMP4 |视频:h264、1280×720 |音频:AAC,44.1 KHz,2通道 类型:在线学习 |语言: 英语 |持续时间: 13 讲座 ( 4h 8m ) |大小: 1.3 GB基于 Python 的机器学习课程,包含实践