mostafa elsayed

Original address: http://www.cnblogs.com/cyruszhu/p/5496913.htmlDo not use for commercial use without permission! For related requests, please contact the author: [Email protected]Reproduced please attach the original link, thank you.1 BasicsL Andrew NG's machine learning video.Connection: homepage, material.L 2.2008-year Andrew Ng CS229 machine LearningOf course, the basic method does not change much, so the courseware PDF downloadable is the advantage.Chinese subtitles video @ NetEase Open cla

environment. 4. Add friends Wave is a new thing, so when you first enter the wave, there are usually fewer friends in the contact list. They are all G talk contacts with wave accounts. to expand the scope of communication, you can add a friend using the following method: ■Find a friend who already has a wave account: Click the plus sign on the contact list, copy the account of the TA, and click Submit. ■Friends who appear in the Wave: In the wave you are participating in

Migrate data in Entity Framework 7, entityframework (This article is also published in my public account "dotNET daily excellent article". Welcome to the QR code on the right to follow it .) Question: Although EF7 re-designs the Entity Framework, it still supports data migration. Entity Framework 7 is a rebirth of the Microsoft ORM Framework and becomes more lightweight. Therefore, the Migration function is not enabled by default, that is, the created database does not contain the "_ MigrationHi

brief overview of the library. Go through lecture to lecture for CS109 course from Harvard. You'll go through an overview of machine learning, supervised learning algorithms like regressions, decision Trees, Ense Mble Modeling and non-supervised learning algorithms like clustering. Follow individual lectures with the assignments from those lectures.Additional Resources: If There is a book, you must read, it's programming collective Intelligence–a Classic, but still one of the best book

better to look at it from the beginning, the difficulty is optimization. The second-level planning solution requires a large amount of computing. in practical applications, the SMO (Sequential minimal optimization) algorithm is commonly used. The SMO algorithm is intended to be placed in the next section in combination with the code. References: [1] machine learning in action. Peter Harrington [2] Learning From Data. Yaser S. Abu-Mostafa The above is

) , you can also follow one of the best courses onmachine learning course from Yaser Abu-mostafa. If you need more lucid explanation for the techniques, you can opt for Themachine learning course from Andrew Ng and follow The exercises on Python. tutorials (Individual guidance) On Scikit Learn Assignment: Try out this challenge on KaggleStep 7:practice, practice and practiceCongratulations, you made it!You are now having all the need

onmachine learning course from Yaser Abu-mostafa. If you need more lucid explanation for the techniques, you can opt for Themachine learning course from Andrew Ng and follow The exercises on Python. tutorials (Individual guidance) On Scikit Learn Assignment: Try out this challenge on KaggleStep 7:practice, practice and practiceCongratulations, you made it!You are now having all the need in technical skills. It is a matter of practice

highlight. However, the biggest feature is the wide coverage, written very easy to understand. Even with Bayesian this formula is relatively many, the concept of relative around the expression, Bishop still juchongruoqing, writing fluent, voluminous. So it's great for getting started.4. Machine Learning-a Probabilistic PerspectivAuthor: Kevin P. MurphyPublisher: the MIT PressReviews: Views are between the Bayesian upstairs Prml and the ESL frequentist upstairs, 1000+ page, cover surface is very

CS109 Course. Step 5: Useful data visualization Take part in this course of CS109. You can skip the front 2 minutes, but the contents are dry. You can follow this task to complete the course of study. Step 6: Learn the Scikit-learn library and machine learning content Now, we're going to start learning the real part of the whole process. Scikit-learn is the most useful Python library in the field of machine learning. Here is a brief overview of the library. Completing the Harvard CS109 Course 1

mainly explain the knowledge of linear algebra, using the Octave library. Caltech learning from data at the California Institute of Technology: You can take this course on edx, which is explained by Yaser Abu-mostafa. All course videos and materials are available on the California Institute of Technology website. Similar to the Stanford curriculum, you can schedule your studies to complete your homework and small essays according to yo

watch all the course videos at any time, download handouts and notes from Stanford CS229 course. This course includes homework and small tests, which mainly explain the knowledge of linear algebra, using the Octave library. Caltech learning from data at the California Institute of Technology: You can take this course on edx, which is explained by Yaser Abu-mostafa. All course videos and materials are available on the California Institu

In the last 20 blog posts, many machine learning algorithms have been involved, and the appetite has been exhausted. I decided to officially start the system-based Machine Learning Theory and try to enter the practical stage, cover: Professor Yaser Abu-Mostafa of Caltech focuses on traditional statistical theory. Professor Andrew Ng of Stanford U focuses on practical and intuitive machine learning. Professor Geoffery Hinton of the University of Tor

, where RIt is a learning rate set by yourself. If it is too large, it will cause learning shaking. The inverted triangle is the gradient. In addition, the output layer does not have to use the objective functions (Figure 6). You can specify different objective functions as needed, even if you add an support vector machine to the final output, as long as you can perform the export, just get the gradient. In fact, one of Hinton's disciples is doing this recently. I use my own wisdom to improve th

in formula 4: (Formula 4) Obtain the formula shown in (formula 5) by using the formula of the Laplace multiplier: (Formula 5) In formula 5, we use the Laplace multiplier function to evaluate the derivation of W and B, respectively. To obtain the extreme point, let the derivative be 0 and get And then place them in the formula (formula 6) of the Laplace multiplier: (Formula 6) (Formula 6) the last two rows are the optimization functions to be solved. Now we only need to make a secondary pla