coursera cost machine learning

Open Course address: https://class.coursera.org/ml-003/class/index INSTRUCTOR: Andrew Ng1. unsupervised learning introduction (Introduction to unsupervised learning) We mentioned one of the two main branches of machine learning-supervised learning. Now we need to start

Blog has migrated to Marcovaldo's blog (http://marcovaldong.github.io/)Just completed the last week of Cousera on machine Learning , this week introduced one of the applications of machine learning: Photo OCR (optimal character recognition, Optical character recognition), follow the notes below.Photo Ocrproblem Descrip

=[] For C in Cs: # Select Model CLS = Logisticregression (c=c) # submit data to Model training Cls.fit (X_train, Y_train) Scores.append (Cls.score (X_test, Y_test)) # # Drawing Fig=plt.figure () Ax=fig.add_subplot (1,1,1) ax.pl OT (cs,scores) ax.set_xlabel (r "C") Ax.set_ylabel (r "Score") Ax.set_xscale (' Log ') Ax.set_title ("Logisticregression") plt.show () If __name__== ' __main__ ': X_train,x_test,y_train,y_test=load_data () # Generates a dataset for regression problems Test_logist

? Get more training data? Trying to use a smaller set of features? Trying to use more features? Trying to increase $\lambda$? Trying to reduce $\lambda$? What do you do with the above practices? Do you rely on intuition?In reality, people often rely on intuition to pick a particular practice, such as getting more training data, but when they spend a lot of time to do it, they find that the performance of the model does not improve, relying on intuition is clearly a

After talking about the tree in the data structure (for details, see the various trees in the data structure in the previous blog post), let's talk about the various tree algorithms in machine learning algorithms, including ID3, C4.5, cart, and the tree model based on integrated thinking Random forest and GBDT. This paper gives a brief introduction to the basic ideas of various tree-shape algorithms, and fo

Some of the beginners of Linux operations think that learning Linux needs to install its own computer into a Linux system or need to have a real server device. In fact, beginners can learn Linux operations by using virtual machines. Using virtual machine software to build Linux learning environment is simple and easy to use, it is important that the virtual

of the pre-sorted algorithm, the communication cost is very high, so in parallel is also the use of histogram algorithm, LIGHTGBM using the histogram algorithm communication cost is small, through the use of Set communication algorithm, can achieve parallel computing linear acceleration. LIGHTGBM support category features In fact, most machine

Why machine learning is not good in the investment field Original 2017-04-05 Ishikawa Volume letter Investment Http://mp.weixin.qq.com/s/RgkShbGBAaXoSDBpssf76A “ The essence of data snooping is this focusing on interesting events are quite different from trying to figure out which Eve NTS are interesting. Attention to interesting events and figuring out which events are interesting are two different things,

:", X) - Print("Y:", Y) - innumiterations=100000 -alpha=0.0005 toTheta=np.ones (x.shape[1]) +Theta=graientdescent (x,y,theta,alpha,x.shape[0],numiterations) - Print(Theta)Operation Result:...... Too many output data to intercept only the next more than 10 linesIteration 99988/cost:3.930135Iteration 99989/cost:3.930135Iteration 99990/cost:3.930135Iteration 99991/

successfully convert the nonlinear severalproblem to the linear severalproblem, as shown below: The left side is the original dataset, which is obviously non-linear, but if we process the input, the values of X1 and X2 are the same square, this is equivalent to ing the space on the left to the space on the right. In this way, the nonlinear severalproblem is successfully converted into a linear severalproblem. Note that, when a new X is input, we need to use the same method to convert it first.

value;If it becomes smaller, the new puzzle will replace the original;If it becomes larger, the probability of replacing the old one with the new one depends on the current temperature value, where the temperature will begin to slow down at a relatively high value, which is why the algorithm is more receptive to relatively poor performance in the early stages of execution, so that we can effectively avoid the possibility of falling into the local minimum, when the temperature reaches 0, The alg

/directoryIv. Hardware Configuration RecommendationsIf it is for academic research rather than commercialization, a cost-effective hardware solution is recommended:1, graphics card: Titianx graphics card 2, gtx98ti can also,2, the motherboard can choose to insert a few video cards, generally also thousands of dollars, such as " gigabyte lga2011-3 ga-x99" Chassis and power supply what makes the supplier match up, the entire solution can be controlled b

Now machine learning algorithms in classification, regression, data mining and other issues on the use of a very broad, for beginners, may be heard ' algorithm ' or other exclusive nouns feel inscrutable, so many people are deterred, which makes many people in dealing with a lot of problems lost a very useful tool. Machine le