What 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 2022
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…
Read MoreThe Future of AI & How It will Transform the World?
The future of AI technology is bright. It will affect our lives in many ways and it will change the way we live, work and play. The future is here, and it’s called artificial intelligence. Artificial intelligence is not just a passing fad or buzzword. It’s actually a revolutionary technology that will change the way…
Read MoreMachine Learning Interview questions Part -3
1 – Explain the difference between Variance and R squared error? Variance is a statistical measure of the dispersion of a distribution. It is often used in statistics to measure how much variation or “dispersion” there is from the mean. Variance can be calculated as the average squared deviation from the mean, which for a…
Read MoreHow to Convert text into features?
In this chapter, we’re going to cover introductory to advanced feature engineering (text to features) styles. By the end of this chapter, you’ll be comfortable with the following recipes One Hot encoding Count vectorizer N- grams Hash vectorizer Term Frequency- Inverse Document Frequency (TF- IDF) Implementing word embedding Implementing fastText Now that all the text…
Read MoreImage processing using Machine Learning
We begin this chapter by examining a number of of the foremost image process algorithmic rule, then march on to machine learning implementation in image processing. The chapter at a look is as follows: Feature Mapping using the SIFT algorithmic rule Suppose we’ve 2 pictures. One image is of a bench in an exceedingly park.…
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