实用机器学习

Machine-Learning-Basics

Kaggle正在进行的《泰坦尼克号灾难ML》竞赛 机器学习模型，可预测哪些乘客在泰坦尼克号沉船事故中幸存下来。 该模型的准确度为100％

Mathematics-for-Machine-Learning-Linear-Algebra

机器学习数学（线性代数） 完整播放列表-https: list PL2jykFOD1AWazz20_QRfESiJ2rthDF9- 吉尔伯特·斯特朗（Gilbert Strang）关于线性代数（MIT）的演讲-完整播放列表 点积和投影： 基础，向量空间和线性相关性 矩阵转换 变更依据： https://eli.thegreenplace.net/2015/change-of-basis-in-linear-algebra/ https://www.math.purdue.edu/files/academic/courses/2010spring/MA26200/4-7.pdf 高斯消除： https://www.geeksforgeeks.org/gaussian-elimination/ https://www.codesansar.com/numeric

LAML:Linear Algebra and Machine Learning:一个用于线性代数和机器学习的独立Java库-开源

LAML是用于线性代数和机器学习的独立纯Java库。 目标是建立高效且易于使用的线性代数和机器学习库。 线性代数和机器学习一起构建的原因是，需要对矩阵和向量的基本数据结构进行完全控制，以实现机器学习方法的快速实现。 此外，LAML在与MATLAB相同的签名中提供了许多常用的矩阵函数，因此也可以用于将MATLAB代码手动转换为Java代码。

Basics for Linear Algebra for Machine Learning - Discover the Mathematical

Some classical methods used in the field of linear algebra,such as linear regression via linear least squares and singular-value decomposition, are linear algebra methods, and other methods, such as principal component analysis, were born from the marriage of linear algebra and statistics. To read and understand machine learning, you must be able to read and understand linear algebra. This book helps machine learning practitioners, get on top of linear algebra, fast.

Basics of Linear Algebra for Machine Learning (Python)

Basics of Linear Algebra for Machine Learning: Discover the Mathematical Language of Data in Python By 作者: Jason Brownlee Pub Date: 2018 ISBN: n/a Pages: 212 Language: English Format: PDF Linear ...

Code for Basics of Linear Algebra for Machine Learning.zip

Basics of Linear Algebra for Machine Learning.zip 机器学习的线性代数基础 课程代码

Basics of Linear Algebra for Machine Learning Discover the Mathematical 无水印原版pdf

Basics of Linear Algebra for Machine Learning Discover the Mathematical Language of Data in Python 英文无水印原版pdf pdf所有页面使用FoxitReader、PDF-XChangeViewer、SumatraPDF和Firefox测试都可以打开 ...

[machine_learning_mastery系列]Basics for Linear Algebra for Machine Learning.pdf

When practitioners do circle back to study linear algebra, they learn far more of the field than is required for or relevant to machine learning. Linear algebra is a large field of study that has ...

Jason-Brownlee-deep_learning_with_python(pdf + sourcecode v1.15 2018).zip

Deep learning is the most interesting and powerful machine learning technique right now. Top deep learning libraries are available on the Python ecosystem like Theano and TensorFlow. Tap into their ...

Machine-Learning-Linear-Regression-Project

机器学习线性回归项目

Machine-Learning-Basics:机器学习导论

机器学习基础 机器学习简介： 介绍 监督学习 无监督学习 自动毕业 自然语言处理 监督学习： 回归 线性回归 多项式回归 分类 逻辑回归 决策树 KNN（K最近邻） 无监督学习： 聚类 K均值 均值漂移 您将需要安装Anaconda Distrebution或jupyter笔记本

Machine-Learning-Basics:大致了解ML的途径

机器学习基础 基于macOS版本11.2.1（20D74）M1芯片获得ML粗略视图的路径

MIT18.065 Linear Algebra and Learning from Data

来自教授 GILBERT STRANG 的得力之作

matlab中的pinv代码-Machine-Learning-Linear-Regression-Gradient-Descent:机器学习

matlab中的pinv代码机器学习线性回归梯度下降 #Machine Learning Course Coursera作者：Andrew NG 它包含具有单变量和多变量的线性回归和梯度下降的矢量化实现。 它还包括通过正则方程法的解决方案。 #Regression回归问题是指在一定时间间隔内输出值的问题。 像：我们有一个1000的项目库存，并希望预测在未来3个月中将出售多少这些项目。 ＃成本功能：它可以帮助我们找出最适合我们数据的方式。 由J（theta（0），theta（1）...）表示。 h（x）= theta（0）+ theta（1）+ theta（2）....其中theta（i）是参数该想法是选择theta（i）（其中i = 1,2,3,。 ..n），因此h（x）接近y（这是训练示例的输出）。 因此，（h（x）-y）^ 2必须更小（成本函数的实现单独编写在代码中） #Gardient Descent这是一种算法，可缓慢最小化成本函数并达到最佳假设h（x）以拟合数据 #Normal方程与梯度下降法则相反，Normal方程为我们提供了一种简单的分析方法，可一次性获得输出，最适用于行

CMU的Bhiksha Raj 教授Machine Learning for Signal Processing的课件

CMU的Bhiksha Raj 教授Machine Learning for Signal Processing的课件 Recommended Background DSP – Fourier transforms, linear systems, basic statistical signal processing Linear Algebra – ...

Deep Learning in Python: Master Data Science and Machine Learning with Modern

Linear algebra would help. I will assume familiarity with Python (although it is an easy language to pick up). You will need to have some concept of machine learning. If you know about algorithms ...

Data Science from Scratch - First Principles with Python.2015

■■ Learn the basics of linear algebra, statistics, and probability— and understand how and when they're used in data science ■■ Collect, explore, clean, munge, and manipulate data ■■ Dive into ...

MIT.Press.Deep.Learning.2016

The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. Table of Contents Chapter 1 ...

Data Science from Scratch- First Principles with Python(O'Reilly,2015)

Learn the basics of linear algebra, statistics, and probability—and understand how and when they’re used in data science Collect, explore, clean, munge, and manipulate data Dive into the ...

Machine Learning Linear Regression-线性回归

Machine Learning Linear Regression-线性回归

Linear.Algebra.and.Learning.from.Data_machinglearning_data_linea

Linear Algebra and Learning from data by Gilbert Strange pdf

deep learning

• Chapter 5 : Machine Learning Basics • Chapter 6 : Deep Feedforward Networks • Chapter 7 : Regularization for Deep Learning • Chapter 8 : Optimization for Training Deep Models • Chapter 9 : ...

deeplearning part1

deeplearning Part I Applied Math and Machine Learning Basics linear algebra

Data Science from Scratch : First Principles with Python

Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals...

Data Science from Scratch First Principles with Python

Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the ...

Data.Science.from.Scratch.First.Principles.with.Python

Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals...

Data Science from Scratch

This book provides you with the know-how to dig those answers out., Get a crash course in Python, Learn the basics of linear algebra, statistics, and probability—and understand how and when they're ...