Computer Vision for Beginners – Part 3
You may be already familiar with the word ‘contour.’ I’ve used this term several times in previous posts. A contour line is a curved line representing values. It is a very simple type of map that outlines the changes in an area, typically separating the different landforms. But then you may ask this. The terms ‘edges’…
Read MoreComputer Vision for Beginners – Part 2
Today we’re going to talk about how to manipulate images. These are preprocessing steps. When it comes to detecting edges and contours, noise plays a major role in the accuracy of the detection process. -The model needs to focus on the general details of their images in order to produce higher accuracies. -Blurring, thresholding, and…
Read MoreComputer Vision for Beginners – Part 1
Image Processing is used to perform some operations on images in order to animate them, develop videos, or generate graphics. To get started with data analysis, you can use image preprocessing feature engineering. It’s not difficult to extract useful information from images – this is accomplished via image processing methods. Reduction of noise, adjustment of…
Read MoreWhat is doc2vec and word2vec in NLP?
Doc2vec is a technique that extracts semantic information from documents and then uses that information to classify the documents. By applying Doc2vec to existing documents, it becomes possible for AI software to rapidly identify similar topics in a large collection of text without having to read the entire corpus. This technique has been used in…
Read MoreWhat is GD, Batch GD, SGD, Mini-Batch GD?
What is Gradient Descent, Batch Gradient Descent, Stochastic Gradient Descent, Mini-Batch Gradient Descent? Gradient Descent This algorithm is a general algorithm that is used for optimization and for providing the optimal solution for various problems. It takes parameters in an iterative way and makes the cost function as simple as possible. 1) Define a cost…
Read MoreLoss Functions and optimizers and its type?
With modelling, there’s a particular goal that the model needs to achieve. It’s just as important to achieve the best possible values of the model parameters as it is to find out what each parameter means in terms of that goal. The loss function (cost function) is minimized, therefore getting unknown values for weight and…
Read MorePython functions, Parameters, Arguments, args and kwargs
Python functions A function is a construct that helps us perform some action using a block of code (the body of the function), sometime based on input parameters. These functions can take different forms and can do a lot to allow your functional code base to be effective, To define a function, you use the…
Read MoreList comprehensions, break-continue, exception handling in Python
As we have learned for loop to walk through a sequence, and do something with each item, at least read some value from it. There is a scenario, similar to what we saw with the last example in the for-loop introduction, that involves making a new list from the result of doing an operation on…
Read MoreTop 40 Data Science Interview Questions and Answers
1 – What is F1 score? F1 score is a measure of the accuracy of a model. It is defined as the harmonic mean of precision and recall. F1 score is one of the most popular metrics for assessing how well a machine learning algorithm performs on predicting a target variable. F1 score ranges from…
Read MoreWhat is histogram equalizer? How does it work?
Histogram Equalizer is a computer vision technique that adjusts the luminosity levels of an image to make it more visually appealing. Histogram equalization is a process that lets us take an image and adjust the brightness levels so that each pixel in the image has a similar level of illumination. It does this by mapping…
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