NYU Center for Data Science

JUNE 16, 2023

Home to both a thriving tech ecosystem and pioneering efforts on regulating algorithm decision-making systems, New York City provides a vibrant research environment and a plethora of interdisciplinary collaborators,” said Umang. For these reasons, I am excited to start my academic journey at NYU. By Meryl Phair

Machine Learning 108

Machine Learning Explainability Artificial Intelligence Artificial Intelligence 108

IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

Data Science 144

Data Science DevOps Machine Learning Data Scientist 144

Dlabs.ai

JULY 19, 2023

Example: Algorithmic Bias in the UK A-level Grading To illustrate, consider a real-world example that occurred during the COVID-19 pandemic in the UK. With the traditional A-level exams canceled due to health concerns, the UK government used an algorithm to determine student grades.

Explainable AI 97

Explainable AI Explainability Auto-complete Algorithm 97

IBM Journey to AI blog

JULY 17, 2023

While traditional AI approaches provide customers with quick service, they have their limitations. Currently chat bots are relying on rule-based systems or traditional machine learning algorithms (or models) to automate tasks and provide predefined responses to customer inquiries. Watsonx.ai

Generative AI 145

Generative AI Auto-complete AI AI 145

Pickl AI

JANUARY 29, 2024

Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. The collective strength of both forms the groundwork for AI and Data Science, propelling innovation. Opportunities abound in sectors like healthcare, finance, and automation. billion in 2022 to a remarkable USD 484.17 billion by 2029.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

Pickl AI

APRIL 8, 2024

Summary: AI’s immense potential is undeniable, but its journey riddle with roadblocks. This blog explores 13 major AI blunders, highlighting issues like algorithmic bias, lack of transparency, and job displacement. 13 AI Mistakes That Are Worth Your Attention 1.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Algorithm AI 52

IBM Journey to AI blog

JULY 6, 2023

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. Deep learning algorithms are neural networks modeled after the human brain. Some people worry that AI and machine learning will eliminate jobs.

Data Science 148

Data Science Machine Learning Big Data Data Mining 148

Marktechpost

AUGUST 24, 2023

You will never miss any updates on ML/AI/CV/NLP fields because it is posted on a daily basis and highly moderated to avoid any spam. r/Automate The sub has more than 75k members participating in discussions and posts focused on automation. The subreddit has excellent computer vision and artificial intelligence content.

Artificial Intelligence 97

Artificial Intelligence Artificial Intelligence Machine Learning Computer Vision 97

IBM Journey to AI blog

APRIL 11, 2023

In line with this trend, the New York City Council has enacted new regulations requiring organizations to conduct yearly bias audits on automated employment decision-making tools used by HR departments. As per the new law, noncompliant organizations may face fines ranging from no less than USD 500 to no more than USD 1500 for each violation.

AI Strategy 245

AI Strategy Algorithm Automation AI 245

How to Learn Machine Learning

JANUARY 21, 2023

Artificial intelligence (AI) is a term that encompasses the use of computer technology to solve complex problems and mimic human decision-making. At its core, AI relies on algorithms, data processing, and machine learning to generate insights from vast amounts of data. billion by 2027, growing at a CAGR of 36.2%.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Robotics Natural Language Processing 52

Defined.ai blog

AUGUST 10, 2023

From voice assistants like Siri and Alexa, which are now being trained with industry-specific vocabulary and localized dialogue data , to more complex technologies like predictive analytics and autonomous vehicles, AI is everywhere. When it comes to financial data, AI shines brightly. Contact us now to get started.

Business Intelligence 52

Business Intelligence Data Analysis Neural Network AI 52

Mlearning.ai

APRIL 14, 2023

In intelligent automated solutions, users can develop various mental models that affect their understanding and perception regarding the value and quality of an AI system. Human-centered design has expanded from the design of objects to the design of algorithms that determine the behavior of automated or intelligent systems.”

Explainability 52

Explainability AI AI Automation 52

Heartbeat

NOVEMBER 27, 2023

Deep learning automates and improves medical picture analysis. Photo by THAVIS 3D on Unsplash Fundamentals of Deep Learning in Medical Image Analysis Deep learning systems automate and accurately analyze complicated imaging data, revolutionizing medical image analysis.

Deep Learning 59

Deep Learning Convolutional Neural Networks Explainability Neural Network 59

Dlabs.ai

MAY 22, 2022

It’ll help you get to grips with the fundamentals of ML and its respective algorithms, including linear regression and supervised and unsupervised learning, among others. That’s why it helps to know the fundamentals of ML and the different learning algorithms before you do any data science work.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Neural Network 52

Viso.ai

MAY 10, 2024

Basic types of machine learning models Some common types of machine learning algorithms include: Regression models (e.g. It may also mean establishing a CI/CD pipeline to automate model updates in the future. text vs images) and (2) the desired output (e.g. a binary classification or a bounding box for an image).

Machine Learning 52

Machine Learning Computer Vision Neural Network Convolutional Neural Networks 52

AWS Machine Learning Blog

NOVEMBER 9, 2023

We build a model to predict the severity (benign or malignant) of a mammographic mass lesion trained with the XGBoost algorithm using the publicly available UCI Mammography Mass dataset and deploy it using the MLOps framework. This will enable us to test the pattern to trigger automated retraining of the model. csv dataset.

Data Drift 99

Data Drift Auto-complete ML Automation 99

IBM Journey to AI blog

FEBRUARY 8, 2023

For many of today’s organizations today, governing AI requires a lot of manual work that include the use of multiple tools, applications and platforms. Lack of automation can lead to lengthy model approval, validation and deployment cycles during which model drift and bias can happen.

Responsible AI 130

Responsible AI Explainability Automation Explainable AI 130

Viso.ai

MARCH 26, 2024

2: Automated Document Analysis and Processing No.3: 4: Algorithmic Trading and Market Analysis No.5: Viso Suite is the Computer Vision Enterprise Platform Computer Vision Algorithms for Finance Models like YOLO (You Only Look Once) models and Faster R-CNN have set benchmarks in real-time processing as well.

Computer Vision 52

Computer Vision Neural Network Machine Learning Convolutional Neural Networks 52

Viso.ai

APRIL 25, 2024

Studies revealed that the error rate for dark-skinned individuals could be 18 times higher than that for light-skinned individuals in some commercial gender classification algorithms. Facial recognition algorithms are one of the areas affected by the sampling bias, as it can cause different error rates depending on the data it was trained on.

Computer Vision 52

Computer Vision Categorization Algorithm Explainability 52

IBM Journey to AI blog

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Explainable AI — Explainable AI is achieved when an organization can confidently and clearly state what data an AI model used to perform its tasks.

Data Scientist 207

Data Scientist Metadata Responsible AI Explainability 207

IBM Journey to AI blog

SEPTEMBER 20, 2023

They use self-supervised learning algorithms to perform a variety of natural language processing (NLP) tasks in ways that are similar to how humans use language (see Figure 1). Large language models (LLMs) have taken the field of AI by storm.

Large Language Models 225

Large Language Models DevOps AI Modeling Automation 225

Mlearning.ai

SEPTEMBER 5, 2023

Automated Discovery No more waiting around for manual analysis. InsightsAct’s AI engine works continuously in the background to surface relevant insights. Contextual Recommendations InsightsAct doesn’t just identify issues; its algorithms go further by providing contextual recommendations to address uncovered opportunities.

Business Intelligence 52

Business Intelligence Automation AI AI 52

Flipboard

JUNE 20, 2023

Understanding AI’s mysterious “opaque box” is paramount to creating explainable AI. This can be simplified by considering that AI, like all other technology, has a supply chain. When you dissect AI’s supply chain, at the root, you will find algorithms. What factors does it weigh?

AI Modeling 97

AI Modeling Explainability Algorithm Machine Learning 97

The MLOps Blog

JUNE 27, 2023

For example, if your team works on recommender systems or natural language processing applications, you may want an MLOps tool that has built-in algorithms or templates for these use cases. This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics.

Machine Learning 134

Machine Learning Metadata Data Quality Data Scientist 134

IBM Journey to AI blog

JUNE 28, 2023

Most individual omics informatics tools and algorithms focus on solving a specific problem, which is usually part of a large project. This forces organizations to integrate multiple tools into a single pipeline to serve various goals. gene expression; microbiome data) and any tabular data (e.g.,

Data Analysis 168

Data Analysis Explainable AI Data Scientist AI Strategy 168

Viso.ai

DECEMBER 6, 2023

Computer vision (CV) is a rapidly evolving area in artificial intelligence (AI), allowing machines to process complex real-world visual data in different domains like healthcare, transportation, agriculture, and manufacturing. The purpose is to give you an idea of modern computer vision algorithms and applications. Get a demo here.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Categorization 52

AI Impacts

DECEMBER 22, 2022

Which might happen because different locales have similar interests (all rational governments should be similarly concerned about losing power to automated power-seeking systems with unverifiable goals), or because—as with individuals—there are social dynamics which support norms arising in a non-centralized way.

AI 130

AI AI AI Researcher AI Research 130

Pickl AI

MARCH 31, 2024

Summary: Generative AI isn’t magic, but it learns like one! This powerful technology utilizes deep learning algorithms to analyze massive amounts of data, be it text, images, or code. Through a multi-step process, the AI extracts patterns and relationships within the data. That’s the magic of generative AI.

Generative AI 52

Generative AI Deep Learning AI AI 52

Pickl AI

MAY 15, 2024

Automate model training, testing, deployment, and monitoring processes to ensure model performance and rapid iteration cycles. However, it’s crucial to understand the underlying algorithms and limitations of AutoML tools.

Data Scientist 52

Data Scientist Data Science Machine Learning Data Quality 52

Unite.AI

NOVEMBER 29, 2023

AI technologies, encompassing the analysis of vast datasets and the identification of patterns, offer invaluable insights, thereby defending the electoral process against manipulation. At the core of countering disinformation lies the emergence of AI watchdogs.

Responsible AI 195

Responsible AI AI AI Algorithm 195

Pickl AI

APRIL 2, 2024

Predictive Analytics: Forecasting future outcomes based on historical data and statistical algorithms. Machine Learning: Subset of AI that enables systems to learn from data without being explicitly programmed. Explainable AI (XAI): As AI models become more complex, there’s a growing need for interpretability.

Data Science 52

Data Science Data Scientist Machine Learning Big Data 52

IBM Journey to AI blog

FEBRUARY 9, 2024

According to a recent IBM survey of over 1,000 employees at enterprise-scale companies , the top three factors driving AI adoption were advances in AI tools that make them more accessible, the need to reduce costs and automate key processes and the increasing amount of AI embedded into standard off-the-shelf business applications.

AI 262

AI AI Generative AI Artificial Intelligence 262