Dataconomy

MARCH 14, 2023

One major issue with conventional supervised learning approaches is that they lack scalability. On the other hand, self-supervised learning can utilize audio-only data, which is more readily available across a wide range of languages. This necessitates a flexible, efficient, and generalizable learning algorithm.

Natural Language Processing 70

Natural Language Processing Machine Learning Machine Learning Supervised Learning 70

Machine Learning (Theory)

APRIL 23, 2021

Welcome to ALT Highlights, a series of blog posts spotlighting various happenings at the recent conference ALT 2021 , including plenary talks, tutorials, trends in learning theory, and more! To reach a broad audience, the series will be disseminated as guest posts on different blogs in machine learning and theoretical computer science.

Computer Science 130

Computer Science Computer Science Machine Learning Machine Learning 130

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 60

Machine Learning Machine Learning Data Science Big Data 60

ODSC - Open Data Science

SEPTEMBER 19, 2023

Then identifying issues that allow fine-tuning of code, optimizing algorithms, and making strategic use of parallel processing. Depending on the position, and company, it can require a strong understanding of natural language processing, computer science, linguistics, and software engineering.

Natural Language Processing 98

Natural Language Processing Data Science Supervised Learning Computer Science 98

Dataconomy

MARCH 13, 2023

Key concepts of AI The following are some of the key concepts of AI: Data:  AI requires vast amounts of data to learn and improve its performance over time. Algorithms:  AI algorithms are used to process the data and extract insights from it. Develop AI models using machine learning or deep learning algorithms.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

NYU Center for Data Science

JANUARY 25, 2024

Andrew Wilson (Associate Professor of Computer Science and Data Science) “ A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning ” by Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C.

Computer Science 73

Computer Science Computer Science Data Science Supervised Learning 73

IBM Journey to AI blog

DECEMBER 20, 2023

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. What is machine learning? ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning Clustering 82

NYU Center for Data Science

NOVEMBER 15, 2023

Pinheiro, Joshua Rackers, Joseph Kleinhenz, Michael Maser, *Omar Mahmood (PhD alumnus), Andrew Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi “A Logic for Expressing Log-Precision Transformers” : *William Merrill (PhD student), Ashish Sabharwal “A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks” : Vignesh Kothapalli, Tom (..)

Data Science 82

Data Science Computer Science Computer Science Supervised Learning 82

Pickl AI

JANUARY 12, 2023

This Data Science professional certificate program is industry-recognized and incorporates all the fundamentals of Data Science along with Machine Learning and its practical applications. The Udacity’s Data Science and Machine Learning course covers a wide range of topics in Data Science and Machine Learning.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Hacker News

MARCH 25, 2022

Transformers made self-supervised learning possible, and AI jumped to warp speed,” said NVIDIA founder and CEO Jensen Huang in his keynote address this week at GTC. Transformers are in many cases replacing convolutional and recurrent neural networks (CNNs and RNNs), the most popular types of deep learning models just five years ago.

Machine Learning 182

Machine Learning Machine Learning AI AI 182

Towards AI

APRIL 4, 2024

Created by the author with DALL E-3 Machine learning algorithms are the “cool kids” of the tech industry; everyone is talking about them as if they were the newest, greatest meme. Amidst the hoopla, do people actually understand what machine learning is, or are they just using the word as a text thread equivalent of emoticons?

K-nearest Neighbors 74

K-nearest Neighbors Machine Learning Machine Learning Decision Trees 74

Pickl AI

APRIL 10, 2023

With the growing proliferation and impact of data-driven decisions on different industries, having expertise in the Data Science domain will always have a positive impact. Student Go for Data Science Course? Yes, BSE students can opt for Data Science courses. Is Data Science for Working Professionals a Good Option?

Data Science 52

Data Science Machine Learning Machine Learning Python 52

Snorkel AI

OCTOBER 31, 2023

The Snorkel papers cover a broad range of topics including fairness, semi-supervised learning, large language models (LLMs), and domain-specific models. This paper explores fairness in weak supervision and presents an empirically validated model of fairness that captures labeling function bias.

Supervised Learning 59

Supervised Learning AI AI Machine Learning 59

IBM Journey to AI blog

JULY 6, 2023

These computer science terms are often used interchangeably, but what differences make each a unique technology? To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. Technology is becoming more embedded in our daily lives by the minute.

Deep Learning 63

Deep Learning Deep Learning Machine Learning Machine Learning 63

DrivenData Labs

JUNE 14, 2023

Accurate and performant algorithms are critical in flagging and removing inappropriate content. Self-supervision: As in the Image Similarity Challenge , all winning solutions used self-supervised learning and image augmentation (or models trained using these techniques) as the backbone of their solutions.

Supervised Learning 173

Supervised Learning Artificial Intelligence Artificial Intelligence AI 173

AssemblyAI

NOVEMBER 21, 2022

Finding efficient and fast matrix multiplication algorithms is therefore paramount given that they will supercharge every neural network, potentially allowing us to run models prohibited by our current hardware limitations. Recently, DeepMind devised a method to automatically discover new faster matrix multiplication algorithms.

Algorithm 52

Algorithm Supervised Learning Deep Learning Deep Learning 52

Becoming Human

MARCH 16, 2023

AI began back in the 1950s as a simple series of “if, then rules” and made its way into healthcare two decades later after more complex algorithms were developed. Since the advent of deep learning in the 2000s, AI applications in healthcare have expanded. A few AI technologies are empowering drug design.

AI 139

AI AI Artificial Intelligence Artificial Intelligence 139

AWS Machine Learning Blog

SEPTEMBER 8, 2023

Image processing and anomaly detection pipeline The following figure demonstrates the detailed overview of our proposed approach that includes the data processing pipeline and various ML algorithms employed for anomaly detection. Precision measures how well our algorithm identifies only anomalies. Having received his B.S.

Machine Learning 86

Machine Learning Machine Learning AWS ML 86

ODSC - Open Data Science

FEBRUARY 14, 2023

The model was fine-tuned to reduce false, harmful, or biased output using a combination of supervised learning in conjunction to what OpenAI calls Reinforcement Learning with Human Feedback (RLHF), where humans rank potential outputs and a reinforcement learning algorithm rewards the model for generating outputs like those that rank highly.

Database 124

Database AI AI Natural Language Processing 124

Snorkel AI

MARCH 1, 2023

Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. What is self-supervised learning? Self-supervised learning is a kind of machine learning that creates labels directly from the input data. Find out in the guide below.

Natural Language Processing 83

Natural Language Processing Supervised Learning Machine Learning Machine Learning 83

Applied Data Science

MARCH 11, 2022

Then, we will look at three recent research projects that gamified existing algorithms by converting them from single-agent to multi-agent: ?️‍♀️ Our internal agents are playing games until they learn how to cooperate and trick us into believing we are an individual. All the rage was about algorithms for classification.

AI 130

AI AI Data Science Machine Learning 130

Hacker News

FEBRUARY 14, 2023

And many of the practical challenges around neural nets—and machine learning in general—center on acquiring or preparing the necessary training data. In many cases (“supervised learning”) one wants to get explicit examples of inputs and the outputs one is expecting from them. But that’s not the case.

Machine Learning 182

Machine Learning Machine Learning Algorithm Artificial Intelligence 182

Pickl AI

APRIL 2, 2024

Data science is the process of extracting the valuable minerals – the insights – that can transform your business. It’s a blend of statistics, computer science, and domain knowledge used to extract knowledge and create solutions from data. Data science for business leaders isn’t about becoming a coding pro.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52