udacity machine learning course

converge or even diverge. .One thing worth noting:As we approach the local minimum, the guide values will automatically become smaller, so the gradient drop will automatically take a smaller amplitude, which is the practice of gradient descent. So there's actually no need to reduce the alpha in addition, we need a fixed (constant) learning rate α. 4. Gradient Descent linear regression (Gradient descent for Linear Regression) This is the method of us

a machine learning framework, the shared parameter model is stored in a hash table and is updated with a deferred consistency protocol, which determines that Petuum has 1 to 2 orders of magnitude less than parameter server for the size of the cluster and the number of parameters that can be supported. Of course, compared to the Spark mllib list data store and BS

downward change to achieve a minimum point, Whether it is local or global.To describe in a simpler mathematical language step 2) is this:Inverted triangle represents the gradient, in this way to express, θi is gone, look at the use of good vectors and matrices, really will greatly simplify the description of mathematics AH.Summary and preview:The contents of this article are mainly taken from the second episode of Stanford's course, I hope I can make

python Programming Huangge python Remote Video Training Course Article/index. md at master · pythonpeixun/article · GitHub Yellow brother python Training Workshop video playback address Article/python_shiping.md at master · pythonpeixun/article · GitHub I recommend you a book "Collective smart programming". All the examples in this section are written in python. You may learn a lot from them by reading all the code. Compared with python, this

outside world. Of course this is also relative, but in order to achieve our goal, I will delimit the boundary, when we write our own matrix model, data frame or build our own database, we will use Python in the NumPy, Panda and Matplotlib library. In some cases, we won't even use the full functionality of these libraries. We'll talk about it later, so let's put their names in the first place for a better understanding. The features that come with you

Write in front of the crap:Well, I have to say Fish C markdown Text editor is very good, full-featured. Again thanks to the little turtle Brother's python video Let me last year in the next semester of the introduction of programming, fell in love with the programming of the language, because it is biased statistics, after the internship decided to put the direction of data mining, more and more found the importance of specialized courses. In the days when everyone was busy attending various tra

amounts of seemingly unrelated data processing, so need data mining technology to extract a variety of data and variables of the relationship between, so as to refine the data.Data mining is essentially a basis for machine learning and artificial intelligence, and his main goal is to extract the superset information from a variety of data sources, and then merge that information into patterns and relations

This paper mainly records the cost function of neural network, the usage of gradient descent in neural network, the reverse propagation, the gradient test, the stochastic initialization and other theories, and attaches the MATLAB code and comments of the relevant parts of the course work. Concepts of neural networks, models, and calculation of predictive classification using forward propagation refer to Andrew Ng

Label: style blog HTTP Io ar use strong SP data Machine Learning Courses Requirements: Basic linear algebra (matrix, vector, matrix vector multiplication), basic probability (probability of random variables and basic attributes), and Calculus Machine Learning: Course