Data Science Dojo

AUGUST 19, 2024

The demand for AI scientist is projected to grow significantly in the coming years, with the U.S. AI researcher role is consistently ranked among the highest-paying jobs, attracting top talent and driving significant compensation packages. Describe the backpropagation algorithm and its role in neural networks.

AI 258

AI AI Machine Learning Machine Learning 258

Data Science Dojo

MAY 10, 2024

Their impact on ML tasks has made them a cornerstone of AI advancements. Unsupervised vs. supervised learning for embeddings While vector representation and contextual inference remain important factors in the evolution of LLM embeddings, the lens of comparative analysis also highlights another aspect for discussion.

Supervised Learning 259

Supervised Learning Clustering ML ML 259

Data Science Dojo

JULY 2, 2024

Adaptive AI has risen as a transformational technological concept over the years, leading Gartner to name it as a top strategic tech trend for 2023. It is a step ahead within the realm of artificial intelligence (AI). As the use of AI has expanded into various arenas of the world, the technology has also developed over time.

AI 195

AI AI Algorithm Machine Learning 195

AWS Machine Learning Blog

JANUARY 31, 2025

Increasingly, FMs are completing tasks that were previously solved by supervised learning, which is a subset of machine learning (ML) that involves training algorithms using a labeled dataset. George Lee is AVP, Data Science & Generative AI Lead for International at Travelers Insurance.

Supervised Learning 97

Supervised Learning AWS Data Scientist ML 97

Dataconomy

MAY 29, 2023

In the field of AI and ML, QR codes are incredibly helpful for improving predictive analytics and gaining insightful knowledge from massive data sets. These algorithms allow AI systems to recognize patterns, forecast outcomes, and adjust to new situations.

Predictive Analytics 208

Predictive Analytics ML ML Analytics 208

Dataconomy

SEPTEMBER 13, 2023

AI annotation jobs are on the rise; naturally, people started asking what exactly is data annotation. AI annotation jobs: What is data annotation? AI still needs a human hand to operate efficiently; for how long, though? These tasks are indispensable, as algorithms heavily rely on pattern recognition to make informed decisions.

Machine Learning 195

Machine Learning Machine Learning AI AI 195

Pickl AI

APRIL 3, 2023

Accordingly, Machine Learning allows computers to learn and act like humans by providing data. Apparently, ML algorithms ensure to train of the data enabling the new data input to make compelling predictions and deliver accurate results. Therefore, Supervised Learning vs Unsupervised Learning is part of Machine Learning.

Supervised Learning 52

Supervised Learning Machine Learning Machine Learning Clustering 52

Pickl AI

FEBRUARY 17, 2025

This scenario highlights a common reality in the Machine Learning landscape: despite the hype surrounding ML capabilities, many projects fail to deliver expected results due to various challenges. Statistics reveal that 81% of companies struggle with AI-related issues ranging from technical obstacles to economic concerns.

Machine Learning 52

Machine Learning Machine Learning Supervised Learning ML 52

Towards AI

APRIL 8, 2024

Last Updated on April 8, 2024 by Editorial Team Author(s): Eashan Mahajan Originally published on Towards AI. Photo by Arseny Togulev on Unsplash With machine learning’s surge of popularity in the past few years, more and more people spend hours each day trying to learn as much as they can. Let’s get right into it.

Supervised Learning 105

Supervised Learning Machine Learning Machine Learning Clustering 105

Google Research AI blog

FEBRUARY 10, 2023

Robust algorithm design is the backbone of systems across Google, particularly for our ML and AI models. Hence, developing algorithms with improved efficiency, performance and speed remains a high priority as it empowers services ranging from Search and Ads to Maps and YouTube. You can find other posts in the series here.)

Algorithm 110

Algorithm Clustering ML ML 110

Towards AI

JULY 3, 2024

Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. When it comes to the three best algorithms to use for spatial analysis, the debate is never-ending. Although practitioners’ tastes may differ, several algorithms are regularly preferred because of their strength, adaptability, and efficiency.

K-nearest Neighbors 105

K-nearest Neighbors Machine Learning Machine Learning Algorithm 105

Data Science Dojo

MAY 10, 2024

Their impact on ML tasks has made them a cornerstone of AI advancements. Read on to understand the role of embeddings in generative AI Let’s take a step back and travel through the journey of LLM embeddings from the start to the present day, understanding their evolution every step of the way.

Supervised Learning 195

Supervised Learning Clustering ML ML 195

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 160

Internet of Things Artificial Intelligence Artificial Intelligence AI 160

NYU Center for Data Science

SEPTEMBER 13, 2024

The world of multi-view self-supervised learning (SSL) can be loosely grouped into four families of methods: contrastive learning, clustering, distillation/momentum, and redundancy reduction. I don’t think it will replace existing algorithms,” Shwartz-Ziv noted.

Supervised Learning 68

Supervised Learning Machine Learning Machine Learning Clustering 68

Data Science Dojo

JULY 4, 2024

Generative AI applications like ChatGPT and Gemini are becoming indispensable in today’s world. What is Reinforcement Learning from Human Feedback Reinforcement Learning from Human Feedback is a cutting-edge machine learning technique used to enhance the performance and reliability of AI models.

AI 195

AI AI Algorithm Natural Language Processing 195

Towards AI

SEPTEMBER 3, 2024

Last Updated on September 3, 2024 by Editorial Team Author(s): Surya Maddula Originally published on Towards AI. Let’s discuss two popular ML algorithms, KNNs and K-Means. They are both ML Algorithms, and we’ll explore them more in detail in a bit. Join thousands of data leaders on the AI newsletter.

K-nearest Neighbors 111

K-nearest Neighbors Clustering Supervised Learning ML 111

Dataconomy

APRIL 18, 2023

With the rise of AI-generated art and AI-powered chatbots like ChatGPT, it’s clear that artificial intelligence has become a ubiquitous part of our daily lives. These cutting-edge technologies have captured the public imagination, fueling speculation about the future of AI and its impact on society.

Artificial Intelligence 113

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 113

Dataconomy

OCTOBER 5, 2023

If you are interested in technology at all, it is hard not to be fascinated by AI technologies. Whether it’s pushing the limits of creativity with its generative abilities or knowing our needs better than us with its advanced analysis capabilities, many sectors have already taken a slice of the huge AI pie.

AI 136

AI AI Artificial Intelligence Artificial Intelligence 136

Towards AI

JANUARY 11, 2024

Last Updated on January 12, 2024 by Editorial Team Author(s): Davide Nardini Originally published on Towards AI. Arguably, one of the most important concepts in machine learning is classification. This article will illustrate the difference between classification and regression in machine learning. Published via Towards AI

Machine Learning 130

Machine Learning Machine Learning Decision Trees Supervised Learning 130

Dataconomy

AUGUST 31, 2023

Machine learning models have already started to take up a lot of space in our lives, even if we are not consciously aware of it. Embracing AI systems and technology day by day, humanity is experiencing perhaps the fastest development in recent years. You want an example: ChatGPT, Alexa, autonomous vehicles and many more on the way.

Machine Learning 136

Machine Learning Machine Learning Supervised Learning Algorithm 136

Google Research AI blog

MARCH 6, 2023

First, there is a lack of scalability with conventional supervised learning approaches. In contrast, self-supervised learning can leverage audio-only data, which is available in much larger quantities across languages. This requires the learning algorithm to be flexible, efficient, and generalizable.

Supervised Learning 140

Supervised Learning AI AI Algorithm 140

IBM Journey to AI blog

DECEMBER 20, 2023

That’s why diversifying enterprise AI and ML usage can prove invaluable to maintaining a competitive edge. Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. What is machine learning? Here, we’ll discuss the five major types and their applications.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

Towards AI

APRIL 7, 2024

Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. Created by the author with DALL E-3 Statistics, regression model, algorithm validation, Random Forest, K Nearest Neighbors and Naïve Bayes— what in God’s name do all these complicated concepts have to do with you as a simple GIS analyst?

Machine Learning 105

Machine Learning Machine Learning K-nearest Neighbors Supervised Learning 105

Dataconomy

MAY 4, 2023

From predicting disease outbreaks to identifying complex medical patterns and helping researchers develop targeted therapies, the potential applications of machine learning in healthcare are vast and varied. What is machine learning? From personalized medicine to disease prevention, the possibilities are endless.

Machine Learning 192

Machine Learning Machine Learning Algorithm ML 192

AWS Machine Learning Blog

JANUARY 31, 2025

By applying AI to these digitized WSIs, researchers are working to unlock new insights and enhance current annotations workflows. These models are trained using self-supervised learning algorithms on expansive datasets, enabling them to capture a comprehensive repertoire of visual representations and patterns inherent within pathology images.

AWS 109

AWS Supervised Learning ML ML 109

AWS Machine Learning Blog

FEBRUARY 13, 2025

Amazon Bedrock is a fully managed service that makes foundation models (FMs) from leading AI startups and Amazon available through an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case. This is the k-nearest neighbor (k-NN) algorithm. The following figure illustrates how this works.

AWS 111

AWS K-nearest Neighbors Clustering Algorithm 111

Dataconomy

MAY 22, 2023

By dividing the workload and data across multiple nodes, distributed learning enables parallel processing, leading to faster and more efficient training of machine learning models. There are various types of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning.

ML 233

ML ML Machine Learning Machine Learning 233

Smart Data Collective

JUNE 4, 2021

Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. Data scientists use algorithms for creating data models. Whereas in machine learning, the algorithm understands the data and creates the logic. In supervised learning, a variable is predicted.

Data Science 133

Data Science Exploratory Data Analysis Machine Learning Machine Learning 133

Dataconomy

AUGUST 28, 2023

The concept of a kernel in machine learning might initially sound perplexing, but it’s a fundamental idea that underlies many powerful algorithms. Kernels in machine learning serve as a bridge between linear and nonlinear transformations. So how can you use kernel in machine learning for your own algorithm?

Machine Learning 172

Machine Learning Machine Learning Algorithm Support Vector Machines 172

Towards AI

MARCH 11, 2025

Author(s): Arthur Kakande Originally published on Towards AI. Photo by Hyundai Motor Group on Unsplash When we learn from labeled data, we call it supervised learning. When we learn by grouping similar items, we call it clustering. When we learn by observing rewards or gains, we call it reinforcement learning.

Algorithm 54

Algorithm Supervised Learning Clustering AI 54

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

Becoming Human

MARCH 16, 2023

AI drug discovery is exploding. Overhyped or not, investments in AI drug discovery jumped from $450 million in 2014 to a whopping $58 billion in 2021. AI has already helped identify promising candidate therapeutics, and it didn’t take years but months or even days. We will look at success stories, AI benefits, and limitations.

AI 139

AI AI Deep Learning Deep Learning 139

IBM Journey to AI blog

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

IBM Journey to AI blog

MAY 9, 2023

We stand on the frontier of an AI revolution. Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. It sounds like a joke, but it’s not, as anyone who has tried to solve business problems with AI may know.

AI 139

AI AI Data Quality Data Lakes 139

Towards AI

JULY 22, 2023

Last Updated on July 24, 2023 by Editorial Team Author(s): Cristian Originally published on Towards AI. In the context of Machine Learning, data can be anything from images, text, numbers, to anything else that the computer can process and learn from. Instead, it learns by finding patterns and structures in the input data.

ML 98

ML ML Supervised Learning Machine Learning 98

Towards AI

DECEMBER 28, 2023

Last Updated on December 30, 2023 by Editorial Team Author(s): Luhui Hu Originally published on Towards AI. AI Power for Foundation Models (source as marked) As we bid farewell to 2023, it’s evident that the domain of computer vision (CV) has undergone a year teeming with extraordinary innovation and technological leaps.

Supervised Learning 119

Supervised Learning AI AI Algorithm 119

AWS Machine Learning Blog

JULY 18, 2023

The built-in BlazingText algorithm offers optimized implementations of Word2vec and text classification algorithms. The BlazingText algorithm expects a single preprocessed text file with space-separated tokens. Set the learning mode hyperparameter to supervised. For instructions, see Create your first S3 bucket.

Supervised Learning 98

Supervised Learning Algorithm Natural Language Processing AWS 98