vectorization python

1 vectorization (vectorization)In logistic regression, for example, z = w transpose and X for internal product and B, you can use a for loop to implement.But in Python z can call NumPy's method, the direct sentence z = Np.dot (w, x) + B is done with vectorization, and you will find this very fast.Ng made an experiment

When working with arrays of numpy, we should avoid looping as much as possible, using vectorization functions to avoid loops.However, applying a custom function directly above the NumPy array will cause an error, and we need to convert the function to vectorization.def Theta (x): """ Scalar implemenation of the Heaviside step function. """ if x >= 0: return 1 else: return 0Theta (Array ([-3,-2,-1,0,1,2,3]))Error messag

Take ArcGIS, for example, to introduce the techniques of geo-vectorization in combination with your years of work experience.　　First, the registration of the BasemapThere are different registration accuracy requirements for different scale maps:1:200,000 geological map, the registration error can not be higher than 20 meters;1:500,000 geological map, the registration error can not be higher than 50 meters.Scanning quality of the original map, only nee

1 What is auto-vectorizationWe often hear about the automatic vectorization of ArcGIS, what kind of application is there, now for everyone to uncover the mystery!!!ArcScan provides tools to convert scanned images to vector feature layers. The process of converting raster data to vector features is called vectorization. Vectorization can be performed manually by i

As mentioned earlier in the article, the K-means algorithm, the first step is to find the sample points of the cluster. The following are implemented in two ways, one is the normal cycle, and the other is the full vectorization calculation.Assume:X is the MXN sample matrix, each row is a sample, m represents the number of samples, n indicates the number of features;Centroids is the Kxn Matrix, K represents the number of clusters, n represents the numb

1. PrefaceIn the process of natural language processing, it often involves how to measure the similarity between two texts, we all know that the text is a high-dimensional semantic space, how to abstract it, so as to be able to stand in the mathematical perspective to quantify its similarity.With the measurement of similarity between texts, we can use the K-means of partition method, density-based dbscan or model-based probabilistic method to analyze the clustering of text. On the other hand, we

In the vectorization section of the second week, the vectorization process of the gradient descent method is not very clear at first, and it was later deduced and recorded here.The following is the parametric recursive formula for gradient descent (assuming n=2):Equation 1:$\theta_0: = \theta_0-\alpha \frac{1}{m}\sum_{i=1}^{m} (H_\theta (x^{(i)})-y^{(i)}) x^{(i)}_0$$\theta_1: = \theta_1-\alpha \frac{1}{m}\s

The algorithm used by the raster stream vectorization tool is primarily used to vectorize a raster of a river network or any other raster linear network that represents a known direction.The tool has been optimized to use directional rasters to help vectorize intersecting cells and neighboring cells. An adjacent raster stream with the same value of two can be vectorized to two parallel lines. This is in contrast to the raster jog Line (Polyline) tool,

Ufldl learning notes and programming job: vectorization (vectoring/vectoring) Ufldl provides a new tutorial, which is better than the previous one. Starting from the basics, the system is clear and has programming practices. In the high-quality deep learning group, you can learn DL directly without having to delve into other machine learning algorithms. So I started to do this recently. The tutorial, coupled with Matlab programming, is perfect. The a

HT has been praised by customers is its full vectorization design features, vector compared to the traditional picture benefits too much:Www.hightopo.com/guide/guide/core/vector/ht-vector-guide.html The vector can be stepless scale, the interface is not really blurred Text content describing vectors is much smaller than pictures At present, various window.devicepixelratio inconsistent devices, vectors may be the only thorough solution

: Quarethisnumber(5) As you can see from this example,Octave differs from other languages in that the function can return two and more than two values. Example 2 : Calculate its cost function from a small number of datasetsThere is a file named "COSTFUCTIONJ.M" on the desktop with the following contents:Unction J = Costfuctionj (X, y, Thera)m = size (x,1);predictions = X*thera;Sqrerrors = (predictions-y). ^2;J = 1/(2*m) *sum (sqrerrors);Set X = [1 1;1 2;1 3] (the first column is the x0 value, th

Lexical and vectorization of text

63.2. Creation of 22-D arrays1 small-scale array direct inputThis should be more familiar. The first section also reads: Click to open the link2. Medium scale array Array Editor creation method1. Click the icon in the work interval (Workspace) New variable, create a variable named unnamed, double-click the variable name, the following interface appearsBy manually entering data, save it last (preferably saved)For renaming, you can change the variable name by clicking the variable name in the

; Theta_plus (i) =theta_plus (i) +epsilon; Theta_minu (i) =theta_minu (i)-epsilon; Numgrad (i) = (J (theta_plus)-j (Theta_minu))/(2*epsilon); endSTEP4: Visualization, Training train.m , the relevant gradient check related code is removed, because this part of the code is more time consuming. 2 : Vectorization Programming ImplementationThis only needs to be changed slightly in the above code. Step1: first set the parameter toVisiblesize = 28*

) Reference (3), (7), (8) The final result of the formula (18) can be obtained: (19) General (16), (17), (19) The final result of formula (15) can be obtained: (20) --------------------------------------------------------------------------------------------------------- Additionally, the bias of the hidden-layer neurons can be solved by equivalent ideas similar to those described above. Just change the last item of formula (20) to 1 to get the updated formula of the hidden layer neuron bias. ---

Ufldl Study Notes and programming assignments: softmax regression (vectorization acceleration) Ufldl provides a new tutorial, which is better than the previous one. Starting from the basics, the system is clear and has programming practices. In the high-quality deep learning group, you can learn DL directly without having to delve into other machine learning algorithms. So I started to do this recently. The tutorial, coupled with Matlab programming,

This article describes how the pandas series with the index index is vectorized:1. Index indexed arrays are the same:S1 = PD. Series ([1, 2, 3, 4], index=['a','b','C','D']) S2= PD. Series ([ten, +, +], index=['a','b','C','D'])PrintS1 +s2a11b22C33D44Dtype:int64Add the values corresponding to each index directly2. Index indexed array values are the same, in different order:S1 = PD. Series ([1, 2, 3, 4], index=['a','b','C','D']) S2= PD. Series ([ten, +, +], index=['b','D','a','C'])PrintS1 +s2a31b12

1 Projection of imagesTo open the image first, the Toolbox-data Management tools-projections and Transformations-define Projection when selecting the projection with select-projected Coordinate Systems-gauss kruger-xian1980 or generally set to

Grating data files describe pixels, that is, vertices. The file size has a considerable relationship with the resolution. The size of the grating file is equal to that of the drawing of the same format.A vector data file describes a graphic unit,

Mouse In this tutorial, I will show you if the Audio TT car is flashmx2004 by the mouse, although it is flashmx2004, it is also suitable for its flash version. The drawing board is not needed here, but if you are lucky enough to have it, you can