top machine learning books

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Learning new things, is constantly reading a book, until read, or continue to look at new books, and every book you want to know the east?

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Linux Learning Books recommended

Introductory book:"Bird's private Cuisine" (Basic article)"Bird's private Cuisine" (service article)"Linux command line and Shell Scripting Encyclopedia (2nd edition)"Unix/linux System Management Technical ManualThe Art of UNIX programmingcomputer and operating system principle book:In-depth understanding of computer Systems (original book 2nd edition)"Modern Operating System (original book 3rd edition)"deep understanding of Linux systemsprinciple article:"Linux kernel design and implementation

Linux Learning Decision Books

In the first three years of college, I didn't know it would take a lot of time to choose a field to specialize in. It feels as if everything is just a little bit, and it doesn't say anything. At the university's three grade birthday, I decided to take all the time I had to go down and buy the old boy teacher's course, because before I graduated from college, I wanted me to be able to do my own job in the Linux domain, to be able to go to the Institute after college, to read, or to find a good of

Machine Learning School Recruit NOTE 2: Integrated Learning _ Machine learning

What is integrated learning, in a word, heads the top of Zhuge Liang. In the performance of classification, multiple weak classifier combinations become strong classifiers. In a word, it is assumed that there are some differences between the weak classifiers (such as different algorithms, or different parameters of the same algorithm), which results in different classification decision boundaries, which means that they make different mistakes when ma

Web standard learning resources (books, websites) recommend_experience exchange

Recommended Web standard learning resources (books, websites) I. Web standard learning Book recommendation 1. Website reconstruction-Design Based on WEB standards Screen. width * 0.7) {this. resized = true; this. width = screen. width * 0.7; this. style. cursor = 'hand'; this. alt = 'click here to open new window \ nCTRL + Mouse wheel to zoom in/out';} "onclic

Recommended Books for Linux technology learning-that's what Linux should learn

losses, so some people say "setbacks, pain behind the growth of space."While learning, self-struggle is the foundation, but practice and open-minded advice is the key. In the university, I met every setback, every difficulty, there are teachers, friends and classmates of the enthusiastic help, and every little bit of success, also have everyone to share, this is really a great happiness of life. Thank the teacher for their selfless help, thanks to al

Good books and celebrities for Linux kernel learning

A good book and celebrity for Linux kernel learning-general Linux technology-Linux programming and kernel information. The following is a detailed description. I personally think that kernel learning is a good book: 1. deep understanding of Linux kernel: It is easy to understand and suitable for Linux kernel users. 2. A book titled source code analysis of Linux kernel 2.4: The content is comprehensi

Two methods of machine learning--supervised learning and unsupervised learning (popular understanding) _ Machine Learning

Objective Machine learning is divided into: supervised learning, unsupervised learning, semi-supervised learning (can also be used Hinton said reinforcement learning) and so on. Here, the main understanding of supervision and unsu

Stanford Machine Learning video note WEEK6 on machine learning recommendations Advice for applying machines learning

We will learn how to systematically improve machine learning algorithms, tell you when the algorithm is not doing well, and describe how to ' debug ' your learning algorithms and improve their performance "best practices". To optimize machine learning algorithms, you need to

PHP_Bibel reading and learning (1) reading books and reading classics, writing text and writing code-tough

PHP_Bibel reading and learning (1) -- reading books and reading classics, writing text and writing code-Ren also quickly looks at it, and then there are new and interesting reading every day. This book is well received by many people, such as 'php and MySQL Web developer', the mechanical industry Publishing House, and the Australian author. if you are interested, you can take a look. Article 1 use PHP I.

[Machine learning algorithm-python implementation] matrix denoising and normalization, python Machine Learning

in mat: for j in range(0,m): if i[j]>MaxNum[j]: MaxNum[j]=i[j] for p in mat: for q in range(0,m): if p[q] Library implementation: Input matrix mat, GetAverage (mat): returns the mean value. GetVar (average, mat): returns the variance DenoisMat (mat): de-noise AutoNorm (mat): normalization Matrix : Https://github.com/jimenbian/AutoNorm-mat- /******************************** * This article is from the blog "Li bogarvin" * Reprin

Deep understanding of machine learning: from principle to algorithmic learning notes-1th Week 02 Easy Entry __ Machine learning

deep understanding of machine learning: Learning Notes from principles to algorithms-1th week 02 easy to get started Deep understanding of machine learning from principle to algorithmic learning notes-1th week 02 Easy to get star

Forecast for 2018 machine learning conferences and 200 machine learning conferences worth attention in 200

Forecast for 2018 machine learning conferences and 200 machine learning conferences worth attention in 200 2017 is about to pass. How is your harvest this year? In the process of learning, it is equally important to study independently and to learn from others. It is a goo

Getting Started with machine learning-understanding machine learning + Simple perceptron (Java implementation)

First, let's talk about gossip.  If you go to machine learning now, will you go? Is it because you are not interested in this aspect, or because you think this thing is too difficult, you will not learn? If you feel too difficult, very good, believe that after reading this article, you will have the courage to step into the field of machine

Machine Learning-Stanford: Learning note 1-motivation and application of machine learning

The motive and application of machine learningTools: Need genuine: Matlab, free: Octavedefinition (Arthur Samuel 1959):The research field that gives the computer learning ability without directly programming the problem.Example: Arthur's chess procedure, calculates the probability of winning each step, and eventually defeats the program author himself. (Feel the idea of using decision trees)definition 2(Tom

Stanford University public Class machine learning: Advice for applying machines learning-deciding to try next (how to determine the most appropriate and correct method when designing a machine learning system)

If we are developing a machine learning system and want to try to improve the performance of a machine learning system, how do we decide which path we should choose Next?In order to explain this problem, to predict the price of learning examples. If we've got the

Deep Learning Challenge: Extreme Learning Machine (extra-limited learning machine)?

Preface: Today just heard a talk about Extreme learning Machine (Super limited learning machine), the speaker is Elm Huangguang Professor . The effect of elm is naturally much better than the SVM,BP algorithm. and relatively than the current most fire deep learning, it has

[Pattern Recognition and machine learning] -- Part2 Machine Learning -- statistical learning basics -- regularized Linear Regression

Source: https://www.cnblogs.com/jianxinzhou/p/4083921.html1. The problem of overfitting (1) Let's look at the example of predicting house price. We will first perform linear regression on the data, that is, the first graph on the left. If we do this, we can obtain such a straight line that fits the data, but in fact this is not a good model. Let's look at the data. Obviously, as the area of the house increases, the changes in the housing price tend to be stable, or the more you move to the right

Machine learning-----> Google Cloud machine learning platform

1. Google Cloud Machine learning Platform Introduction:The three elements of machine learning are data sources, computing resources, and models. Google has a strong support in these three areas: Google not only has a rich variety of data resources, but also has a strong computer group to provide data storage in the dat

Machine learning 00: How to get started with Python machine learning

We all know that machine learning is a very comprehensive research subject, which requires a high level of mathematics knowledge. Therefore, for non-academic professional programmers, if you want to get started machine learning, the best direction is to trigger from the practice.PythonThe ecology I learned is very help

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