Dataconomy

MARCH 12, 2025

Support Vector Machines (SVM) are a cornerstone of machine learning, providing powerful techniques for classifying and predicting outcomes in complex datasets. What are Support Vector Machines (SVM)? They work by identifying a hyperplane that best separates distinct classes within the data.

Support Vector Machines 91

Support Vector Machines Decision Trees Supervised Learning Machine Learning 91

Smart Data Collective

JUNE 7, 2019

For centuries before the existence of computers, humans have imagined intelligent machines that were capable of making decisions autonomously. At the early era of Artificial Intelligence, programmers tried to teach machines from the definition of logical rules that the machine itself could extend during the execution of the program.

Machine Learning 101

Machine Learning Machine Learning Supervised Learning Support Vector Machines 101

Towards AI

FEBRUARY 20, 2024

I am starting a series with this blog, which will guide a beginner to get the hang of the ‘Machine learning world’. Photo by Andrea De Santis on Unsplash So, What is Machine Learning? Definition says, machine learning is the ability of computers to learn without explicit programming.

Machine Learning 103

Machine Learning Machine Learning ML ML 103

Pickl AI

JULY 12, 2024

Understanding the Basics of AI Artificial Intelligence (AI) represents the capability of machines to imitate intelligent human behaviour. This section delves into its foundational definitions, types, and critical concepts crucial for comprehending its vast landscape. classification, regression) and data characteristics.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Mlearning.ai

APRIL 13, 2023

Before we discuss the above related to kernels in machine learning, let’s first go over a few basic concepts: Support Vector Machine , S upport Vectors and Linearly vs. Non-linearly Separable Data. Support-vector networks. References [1] Cortes, C., & Vapnik, V. Why is it important? — Medium

Machine Learning 52

Machine Learning Machine Learning Data Scientist Support Vector Machines 52

Pickl AI

NOVEMBER 18, 2024

Key Takeaways Machine Learning Models are vital for modern technology applications. Types include supervised, unsupervised, and reinforcement learning. Key steps involve problem definition, data preparation, and algorithm selection. Ethical considerations are crucial in developing fair Machine Learning solutions.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

MAY 31, 2023

Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines.

Data Science 52

Data Science Python Data Scientist Machine Learning 52