Pickl AI

SEPTEMBER 16, 2024

Summary: This blog highlights ten crucial Machine Learning algorithms to know in 2024, including linear regression, decision trees, and reinforcement learning. Each algorithm is explained with its applications, strengths, and weaknesses, providing valuable insights for practitioners and enthusiasts in the field.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Dataconomy

MAY 25, 2023

On the other hand, artificial intelligence is the simulation of human intelligence in machines that are programmed to think and learn like humans. By leveraging advanced algorithms and machine learning techniques, IoT devices can analyze and interpret data in real-time, enabling them to make informed decisions and take autonomous actions.

Internet of Things 161

Internet of Things Artificial Intelligence Artificial Intelligence AI 161

Dataconomy

MARCH 27, 2023

Some of the ways in which ML can be used in process automation include the following: Predictive analytics:  ML algorithms can be used to predict future outcomes based on historical data, enabling organizations to make better decisions. What is machine learning (ML)?

ML 133

ML ML Machine Learning Machine Learning 133

Pickl AI

FEBRUARY 2, 2025

Classification: How it Differs from Association Rules Classification is a supervised learning technique that aims to predict a target or class label based on input features. For instance, a classification algorithm could predict whether a transaction is fraudulent or not based on various features.

Data Mining 52

Data Mining Data Mining Data Mining Decision Trees 52

Smart Data Collective

SEPTEMBER 24, 2019

Robots were often programmed with simple algorithms that were made in BASIC or Cobol. A new generation of robots depend on machine learning technology. There are a number of different ways that robots can learn and improve their functionality. One approach is imitation learning. Adaptability to new trends.

Machine Learning 94

Machine Learning Machine Learning Artificial Intelligence Artificial Intelligence 94

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 Decision Trees Algorithm 52

Dataconomy

MARCH 27, 2023

Some of the ways in which ML can be used in process automation include the following: Predictive analytics:  ML algorithms can be used to predict future outcomes based on historical data, enabling organizations to make better decisions. What is machine learning (ML)?

ML 70

ML ML Machine Learning Machine Learning 70

Data Science 101

OCTOBER 31, 2019

Data is carefully analyzed and using mining algorithms, hidden patterns are extracted from the data. The models created using these algorithms could be evaluated against appropriate metrics to verify the model’s credibility. The choice of these metrics depends on the nature of the problem. Classification. Anomaly Detection.

Data Mining 77

Data Mining Data Mining Data Mining Data Science 77

IBM Journey to AI blog

JULY 6, 2023

Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis. Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Dataconomy

APRIL 4, 2023

Artificial Intelligence (AI) models are the building blocks of modern machine learning algorithms that enable machines to learn and perform complex tasks. These models are designed to replicate the human brain’s cognitive functions, enabling them to perceive, reason, learn, and make decisions based on data.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

Artificial Intelligence (AI) models are the building blocks of modern machine learning algorithms that enable machines to learn and perform complex tasks. These models are designed to replicate the human brain’s cognitive functions, enabling them to perceive, reason, learn, and make decisions based on data.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Pickl AI

JULY 12, 2024

Their interactive nature makes them suitable for experimenting with AI algorithms and analysing data. Here are a few of the key concepts that you should know: Machine Learning (ML) This is a type of AI that allows computers to learn without being explicitly programmed.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

OCTOBER 24, 2024

Key Takeaways Scope and Purpose : Artificial Intelligence encompasses a broad range of technologies to mimic human intelligence, while Machine Learning focuses explicitly on algorithms that enable systems to learn from data. Supervised Learning : This is the most common form of ML, where algorithms learn from labelled data.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

ODSC - Open Data Science

APRIL 26, 2023

AI algorithms can analyze large data sets containing patient health records and find patterns that can point to a specific disease or condition. Synthetic data and creating better records When creating these AI programs, synthetic data is key to anonymous algorithms since they mimic real-world datasets. But that’s not all.

AI 52

AI AI Algorithm Natural Language Processing 52

Pickl AI

AUGUST 1, 2024

This blog covers their job roles, essential tools and frameworks, diverse applications, challenges faced in the field, and future directions, highlighting their critical contributions to the advancement of Artificial Intelligence and machine learning. Insufficient or low-quality data can lead to poor model performance and overfitting.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 23, 2024

Understanding Data Science Data Science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Healthcare Data Science is revolutionising healthcare through predictive analytics, personalised medicine, and disease detection.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

Pickl AI

DECEMBER 4, 2024

Machine Learning Understanding Machine Learning algorithms is essential for predictive analytics. This includes supervised learning techniques like linear regression and unsupervised learning methods like clustering. Staying updated with new trends requires continuous learning.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

APRIL 2, 2024

There are three main types, each serving a distinct purpose: Descriptive Analytics (Business Intelligence): This focuses on understanding what happened. ” Predictive Analytics (Machine Learning): This uses historical data to predict future outcomes. ” or “What are our customer demographics?”

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

How to Learn Machine Learning

MARCH 25, 2025

It plays a crucial role in areas like customer segmentation, fraud detection, and predictive analytics. At the core of machine learning, two primary learning techniques drive these innovations. These are known as supervised learning and unsupervised learning. The data is raw and unstructured.

Supervised Learning 59

Supervised Learning Machine Learning Machine Learning Algorithm 59

The MLOps Blog

MARCH 21, 2023

Machine learning platform in healthcare There are mostly three areas of ML opportunities for healthcare, including computer vision, predictive analytics, and natural language processing. The most important requirement you need to incorporate into your platform for this vertical is the regulation of data and algorithms.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69