Conv2D is a Keras function that is widely used in building CNNs for image processing tasks. In this article, we will discuss Conv2D in detail, including its working principle, code implementation examples, and practical use cases. Find more on use…
Optimization is one of the critical processes in deep learning that helps in tuning the parameters of a model to minimize the loss function. Adam optimizer is one of the widely used optimization algorithms in deep learning that combines the…
Amongst the umpteen mathematical constants in existence, one that is prominent of the lot would be Euler’s number. Distilled after a series of derivations by Leonard Euler in the 18th century, Euler’s number ventured into the world as we know…
In every programming language, one of the most common things are errors. Errors are raised when we a block of code cannot be partially or completely executed as it violates some basic built in logic of the programming language. Errors…
In this article we will learn about a very important hypothesis test – ADF test (Augmented Dickey Fuller test) for time series analysis. Performing this test to know if the data we are working on is stationary or not is…
With the use of machine learning (ML), which is a category of artificial intelligence (AI), software programs can predict outcomes more accurately without having to be specifically trained to do so. Machine Learning has its own lingo and one should…
Regular expressions, also known as regex, are an incredibly powerful tool for searching and manipulating text. Python’s regex library, re, makes it easy to match exact strings and perform other types of text processing tasks. In this article, we will…
Data can be recorded in umpteen formats. There is no universal format which serves as a one size fits all, for data recording. Depending on the purpose or the source from which the data is collected, the format which is…
Autoregressive models (AR models) are a class of statistical models that can be used to analyze time-series data, where the current value of a variable is predicted based on its past values. These models are commonly used in a variety…
Adaboost, short for Adaptive Boosting, is a machine learning algorithm that has gained widespread popularity due to its high accuracy and efficiency. It is a type of ensemble learning method that combines multiple weak classifiers to create a strong classifier.…