udacity machine learning

Public Course address:Https://class.coursera.org/ml-003/class/index INSTRUCTOR:Andrew Ng 1. deciding what to try next ( Determine what to do next ) I have already introduced some machine learning methods. It is obviously not enough to know the specific process of these methods. The key is to learn how to use them. The so-called best way to master knowledge is to put it into practice. Consider the ear

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

This article focuses on the contents of the 1.2Python libraries and functions in the first chapter of the Python Machine learning Time Guide. Learn the workflow of machine learning.I. Acquisition and inspection of dataRequests getting dataPandans processing Data1 ImportOS2 ImportPandas as PD3 ImportRequests4 5PATH = R'E:/python

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

For a given set of data and problems, the machine learning method to solve the problem is generally divided into 4 steps: A Data preprocessing First, you must ensure that the data is in a format that meets your requirements. The standard data format can be used to fuse algorithms and data sources to facilitate matching operations. In addition, you need to prepare specific data formats for

First, the machine learning algorithm engineers need to master the skills Machine Learning algorithm engineers need to master skills including (1) Basic data structure and algorithm tree and correlation algorithm graph and correlation algorithm hash table and correlation algorithm matrix and correlation algorithm

intervention on the results of model training it's a lever. Model does not understand the business, really understand the business is people. What the model can do is to learn from the cost function and sample, and find the optimal fit of the current sample. Therefore, machine learning workers should be appropriate to the needs of the characteristics of some human intervention and "guidance", such as the h

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.

p.s. SVM is more complex, the code is not studied clearly, further learning other knowledge after the supplement. The following is only the core of the knowledge, from the "machine learning Combat" learning summary. Advantages:The generalization error rate is low, the calculation cost is small, the result is easy to ex

"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

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

The concept of extreme learning machineElm is a new fast learning algorithm, for TOW layer neural network, elm can randomly initialize input weights and biases and get corresponding output weights.For a single-hidden-layer neural network, suppose there are n arbitrary samples, where。 For a single hidden layer neural network with a hidden layer node, it can be expressed asWhere, for the activation function,

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)

Machine learning is accelerating the pace of progress, it is time to explore this issue. Ai can really protect our systems in the future against cyber attacks. Today, an increasing number of cyber attackers are launching cyber attacks through automated technology, while the attacking enterprise or organization is still using manpower to summarize internal security findings, and then compare them with exter

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