Key challenges in the data preparation process
Data preparation is a process of manipulating and organizing raw data before analysis. It is typically an iterative process of manipulating raw, unstructured, and...
Data preparation steps – Why do they matter?
Raw data, which are accumulated from various sources in the form of logs, sensor output, government data, medical research data, climate data, geospatial data,...
What makes Python so popular with developers?
According to Python statistics 2020, there were 8.2 million Python developers worldwide. For comparison, in September 2019, there were 7 million Python developers as...
Top 7 data preparation tools
Data preparation is expensive and time-consuming, especially without automated and mature data preparation tools. Traditionally, data scientists write specific preparation scripts to accomplish project-specific...
Why Python is the fastest-growing programming language
Python is a powerful high-level, object-oriented, general-purpose programming language created by Guido van Rossum. It has been widely used recently, as it is suitable...
Pros and cons of the K-Nearest Neighbors (KNN) algorithm
K-Nearest Neighbors (KNN) is a simple yet powerful classification algorithm that classifies based on a similarity measure. This supervised ML algorithm can be used...
Machine Learning: Cloud or On-Premise?
New technologies are always emerging, changing the way people live and work. Artificial intelligence (AI) is a revolutionary technology impacting virtually every industry. Manufacturing,...
Pros and cons of Random Forest Algorithm
Random Forest is an easy-to-use, supervised machine learning algorithm used for classification and regression problems. It can produce a great result, even without hyperparameter...
41 popular Python libraries for various applications
Python is a powerful high-level, interactive, object-oriented scripting language created by Guido Van Rossum in the late 1980s. It is an object-oriented language, meaning...
Pros and cons of Support Vector Machine (SVM)
Support vector machines (SVMs) are effective yet adaptable supervised machine learning algorithms for regression and classification. However, they are typically employed in classification issues.
SVMs...