machine learning bootcamp

Original: http://blog.csdn.net/abcjennifer/article/details/7834256This column (machine learning) includes linear regression with single parameters, linear regression with multiple parameters, Octave Tutorial, Logistic Regression, regularization, neural network, design of the computer learning system, SVM (Support vector machines), clustering, dimensionality reduc

Original handout of Stanford Machine Learning Course This resource is the original handout of the Stanford machine learning course, which is AndrewNg said that a total of 20 PDF files cover some important models, algorithms, and concepts in machine

Machine learning is a comprehensive and applied discipline that can be used to solve problems in various fields such as computer vision/biology/robotics and everyday languages, as a result of research on artificial intelligence, and machine learning is designed to enable computers to have the ability to learn as humans

7 machine learning System Design Content 7 Machine Learning System Design 7.1 Prioritizing 7.2 Error Analysis 7.3 Error Metrics for skewed classed 7.3.1 Precision/recall 7.3.2 Trading off precision and RECALL:F1 score 7.4 Data for machine

As an article of the College (http://xxwenda.com/article/584), the follow-up preparation is to be tested individually. Of course, there have been many tests. Apache Spark itself1.MLlibAmplabSpark was originally born in the Berkeley Amplab Laboratory and is still a Amplab project, though not in the Apache Spark Foundation, but still has a considerable place in your daily GitHub program.ML BaseThe mllib of the spark itself is at the bottom of the three-layer ML base, MLI is in the middle layer, a

some time ago on the Internet to see the Coursera Open Classroom Big Machine learning Cornerstone Course, more comprehensive and clear machine learning needs of the basic knowledge, theoretical basis to explain. There are several more important concepts and ideas in foundation, first review, and then open the follow-up

to the right in this image. We can generally see the two learning curves, the two curves of blue and red are approaching each other. Therefore, if we extend the curve to the right, it seems that the training set error is likely to increase gradually. The cross-validation set error will continue to decline. Of course, we are most concerned with cross-validation set errors or test set errors. So from this picture, we can basically predict that if we co

MATLAB machine learning did not see what tutorial, only a series of functions, had to record:Matlab Each machine learning method is implemented in many ways, and can be advanced configuration (such as the training decision tree when the various parameters set), here due to space limitations, no longer described in deta

WEEK1:Machine learning: A computer program was said to learn from experience E with respect to some class of tasks T and performance measure P, if Its performance on tasks in T, as measured by P, improves with experience E. Supervised learning:we already know what we correct output should look like. Regression:try to map input variables to some continuous function.

"Machine learning" Matlab 2015a self-machine learning algorithm RollupAuthor: Chen Fa St. "Introduction"Today suddenly found that the version of matlab2015a with a lot of classical machine learning methods, simple and easy to use,

1.1 machine learning basics-python deep machine learning, 1.1-python Refer to instructor Peng Liang's video tutorial: reprinted, please indicate the source and original instructor Peng Liang Video tutorial: http://pan.baidu.com/s/1kVNe5EJ 1. course Introduction 2. Machine

ProfileThis article is the first of a small experiment in machine learning using the Python programming language. The main contents are as follows: Read data and clean data Explore the characteristics of the input data Analyze how data is presented for learning algorithms Choosing the right model and

July online April machine learning algorithm class notes--no.1 Objective Machine learning is a multidisciplinary interdisciplinary, including probability theory, statistics, convex analysis, feature engineering and so on. Recently followed the July algorithm to learn the knowledge of

Application Recommendations for machine learningFor a long time, the machine learning notes have not been updated, the last part of the updated neural network. This time we'll talk about the application of machine learning recommendations.Decide what to do nextSuppose we nee

A probe into machine learning1. What is machine learningLearning refers to the skill that a person refines in the course of observing things, rather than learning, machine learning refers to the ability of a computer to gain some experience (i.e. a mathematical model) in a p

[Machine learning algorithm-python implementation] matrix denoising and normalization, python Machine Learning1. The background project is required. We plan to use python to implement matrix denoising and normalization. The numpy mathematical library does not find ideal functions. Therefore, I wrote a de-noise and normalization algorithm in the standard library,

Original address: http://blog.csdn.net/lrs1353281004/article/details/79529818 Sorting out the machine learning-algorithm engineers need to master the basic knowledge of machine learning, and attached to the internet I think that write a better blog address for reference. (Continuous update)

Core ML machine learning, coreml Machine Learning At the WWDC 2017 Developer Conference, Apple announced a series of new machine learning APIs for developers, including visual APIs for facial recognition and natural language proce

Microsoft Azure cloud service introduces the machine learning module. Users only need to upload data and use some algorithm interfaces and R or other language interfaces provided by the machine learning module, you can use Microsoft Azure's powerful cloud computing capabilities to implement your

1. What is machine learningMachine learning is the conversion of unordered data into useful information.The main task of machine learning is to classify and another task is to return.Supervised learning: It is called supervised learning