The term “Automated Machine Learning,” or “AutoML,” refers to a set of tools and methods used to speed up the creation of machine learning models. It automates a variety of processes, including model evaluation, feature selection, hyperparameter tweaking, and data preparation. By automating the intricate and time-consuming processes involved in model creation, AutoML platforms hope to make machine learning accessible to people and businesses without a strong background in data science....

This article discusses how backpropagation works in TensorFlow, one of the most popular deep-learning libraries. Let’s learn about what is backpropagation and the other attributes related to it....

Data Science and its subfields can demoralize you at the initial stage if you’re a beginner. The reason is that understanding the transitions in statistics, programming skills (like R and Python), and algorithms (whether supervised or unsupervised) are tough to remember as well as implement....

Partial autocorrelation functions (PACF) play a pivotal role in time series analysis, offering crucial insights into the relationship between variables while mitigating confounding influences. In essence, PACF elucidates the direct correlation between a variable and its lagged values after removing the effects of intermediary time steps. This statistical tool holds significance across various disciplines, including economics, finance, meteorology, and more, enabling analysts to unveil hidden patterns and forecast future trends with enhanced accuracy....

Often the data received in a machine learning project is messy and missing a bunch of values, creating a problem while we try to train our model on the data without altering it....

When we talk about knowledge representation, it’s like we’re creating a map of information for AI to use. First-order logic (FOL) acts like a special language that helps us build this map in a detailed and organized way. It’s important because it allows us to understand not only facts but also the relationships and connections between objects. In this article, we will discuss the fundamentals of Knowledge Representation in First-Order Logic...

In statistics, Bartlett’s test is used to test if k samples are from populations with equal variances. Equal variances across populations are called homoscedasticity or homogeneity of variances. Some statistical tests, for example, the ANOVA test, assume that variances are equal across groups or samples. The Bartlett test can be used to verify that assumption. Bartlett’s test enables us to compare the variance of two or more samples to decide whether they are drawn from populations with equal variance. It is fitting for normally distributed data. There are several solutions to test for the equality (homogeneity) of variance across groups, including:...

In this article, we will discuss how to find the maximum and minimum value in any given matrix and printing its row and column index in the R Programming language....

Selecting the most relevant characteristics for a given job is the aim of feature selection, a crucial stage in machine learning. Feature Agglomeration and Univariate Selection are two popular methods for feature selection in Scikit-Learn. These techniques aid in the reduction of dimensionality, increase model effectiveness, and maybe improve model performance....

Data Science is an interdisciplinary field that focuses on extracting knowledge from data sets that are typically huge in amount. The field encompasses analysis, preparing data for analysis, and presenting findings to inform high-level decisions in an organization. As such, it incorporates skills from computer science, mathematics, statistics, information visualization, graphic, and business....

In the world of data space, the era of Big Data emerged when organizations are dealing with petabytes and exabytes of data. It became very tough for industries for the storage of data until 2010. Now when the popular frameworks like Hadoop and others solved the problem of storage, the focus is on processing the data. And here Data Science plays a big role. Nowadays the growth of data science has been increased in various ways and one should be ready for the future by learning what data science is and how can we add value to it....

Inductive reasoning, a fundamental aspect of human logic and reasoning, plays a pivotal role in the realm of artificial intelligence (AI). This cognitive process involves making generalizations from specific observations, which AI systems mimic to improve decision-making and predict outcomes. This article explores the mechanics of inductive reasoning in AI, its importance, and its applications across various domains....