Unite.AI

APRIL 9, 2024

Composite AI plays a pivotal role in enhancing interpretability and transparency. Combining diverse AI techniques enables human-like decision-making. Key benefits include: reducing the necessity of large data science teams. enabling consistent value generation. building trust with users, regulators, and stakeholders.

Composite AI 179

Composite AI Explainability Black Box AI Neural Network 179

Pickl AI

NOVEMBER 5, 2024

Summary: Data Science and AI are transforming the future by enabling smarter decision-making, automating processes, and uncovering valuable insights from vast datasets. Bureau of Labor Statistics predicts that employment for Data Scientists will grow by 36% from 2021 to 2031 , making it one of the fastest-growing professions.

Data Science 52

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 52

ODSC - Open Data Science

FEBRUARY 24, 2023

Apache Superset remains popular thanks to how well it gives you control over your data. Algorithm-visualizer GitHub | Website Algorithm Visualizer is an interactive online platform that visualizes algorithms from code. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

Data Analysis 126

Data Analysis Data Science Business Intelligence Python 126

Pickl AI

JANUARY 29, 2024

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. 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.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

Towards AI

JULY 22, 2023

Last Updated on July 24, 2023 by Editorial Team Author(s): Data Science meets Cyber Security Originally published on Towards AI. Now Algorithms know what they are doing and why! Let us go further into the enigmas of Artificial Intelligence, where AI is making waves like never before! SOURCE: [link] A.

Explainable AI 98

Explainable AI Explainability Neural Network Artificial Intelligence 98

IBM Journey to AI blog

SEPTEMBER 20, 2023

Large language models (LLMs) are a class of foundational models (FM) that consist of layers of neural networks that have been trained on these massive amounts of unlabeled data. Large language models (LLMs) have taken the field of AI by storm. Inference serving of this fine-tuned FM was also demonstrated using a Triton server.

Large Language Models 238

Large Language Models DevOps Data Science AI Modeling 238

ODSC - Open Data Science

OCTOBER 24, 2023

There are two aspects to this problem of synthesizing data. Then, how to essentially eliminate training, thus speeding up algorithms by several orders of magnitude? Yet, I haven’t seen a practical implementation tested on real data in dimensions higher than 3, combining both numerical and categorical features.

Categorization 98

Categorization Data Science Neural Network Algorithm 98

IBM Journey to AI blog

FEBRUARY 8, 2023

Manual processes can lead to “black box models” that lack transparent and explainable analytic results. Explainable results are crucial when facing questions on the performance of AI algorithms and models. Documented, explainable model facts are necessary when defending analytic decisions.

Responsible AI 130

Responsible AI Explainability Explainable AI Automation 130

ODSC - Open Data Science

JANUARY 29, 2025

Explainable AI(XAI) Explainable AI emphasizes transparency and interpretability, enabling users to understand how AI models arrive at decisions. Model Explanations: Algorithms provide human-readable summaries of their predictions, aiding user comprehension.

Robotics 40

Robotics Explainable AI Data Scientist Explainability 40

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 119

Machine Learning Explainability Artificial Intelligence Artificial Intelligence 119

How to Learn Machine Learning

APRIL 4, 2025

AI will automate all repetitive tasks which will lead to increasing need for creativity, critical thinking, and problem solving skills. A lot of traditional roles might go away but there will be opportunities from AI. People will have to reskill in new domains like data science, ethics of AI, or human-AI teamwork.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Automation Explainable AI 52

Unite.AI

DECEMBER 1, 2023

Back then we were, like many in the industry, focused on developing new algorithms and—i.e. This leads to more transparent and explainable AI, equipping enterprises to manage bias and deliver responsible outcomes. I see Snorkel becoming a trusted partner for all large enterprises that are serious about AI.

Data Scientist 146

Data Scientist Auto-classification AI AI 146

Marktechpost

MAY 12, 2024

SEON SEON is an artificial intelligence fraud protection platform that uses real-time digital, social, phone, email, IP, and device data to improve risk judgments. It is based on adjustable and explainable AI technology. Its initial AI algorithm is designed to detect errors in data, calculations, and financial predictions.

AI Tools 102

AI Tools Neural Network Artificial Intelligence Artificial Intelligence 102

The MLOps Blog

JUNE 27, 2023

Learn more The Best Tools, Libraries, Frameworks and Methodologies that ML Teams Actually Use – Things We Learned from 41 ML Startups [ROUNDUP] Key use cases and/or user journeys Identify the main business problems and the data scientist’s needs that you want to solve with ML, and choose a tool that can handle them effectively.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

Marktechpost

AUGUST 24, 2023

r/computervision Computer vision is the branch of AI science that focuses on creating algorithms to extract useful information from raw photos, videos, and sensor data. r/datascience It features the latest content and discussions on Data Science and its related fields. There are about 68k members.

Artificial Intelligence 97

Artificial Intelligence Artificial Intelligence Machine Learning Computer Vision 97

Pickl AI

OCTOBER 8, 2024

This blog will explore the concept of XAI, its importance in fostering trust in AI systems, its benefits, challenges, techniques, and real-world applications. What is Explainable AI (XAI)? Explainable AI refers to methods and techniques that enable human users to comprehend and interpret the decisions made by AI systems.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Explainability Explainable AI 52

Pickl AI

SEPTEMBER 17, 2024

This is where AI steps in, offering advanced capabilities in threat detection, prevention, and response. By leveraging Machine Learning algorithms and predictive analytics, AI-powered cybersecurity solutions can proactively identify and mitigate risks, providing a more robust and adaptive defence against cyber criminals.

Machine Learning 52

Machine Learning IDP Algorithm AI 52

ODSC - Open Data Science

FEBRUARY 22, 2024

Machine Learning with XGBoost Matt Harrison | Python & Data Science Corporate Trainer | Consultant | MetaSnake Join one of the leading experts in Python for this upcoming ODSC East session. By the end, you will be ready to harness the platform for advanced spatial analysis and the development of sophisticated AI models.

Machine Learning 52

Machine Learning Data Science Python ML 52

Dlabs.ai

MAY 22, 2022

Machine Learning for Data Science and Analytics Authors: Ansaf Salleb-Aouissi, Cliff Stein, David Blei, Itsik Peer Associate, Mihalis Yannakakis, Peter Orbanz If you ever dreamt of attending classes at Columbia University but never had the chance, this artificial intelligence course focused on ML is the next best thing.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Neural Network 52

ODSC - Open Data Science

DECEMBER 17, 2024

But the growing role of AI is sparking debates about its fairness, transparency, and long-term implications. How AI Shapes Loan Decisions AI algorithms analyze vast amounts of data, including credit histories, employment records, and spending habits, to predict the likelihood of repayment.

Neural Network 52

Neural Network Explainability Algorithm AI 52

Heartbeat

SEPTEMBER 13, 2023

Through several " Explainable Models ," explainability enables users to achieve insights into the inner workings of the models and understand the factors that influence their output. Algorithmic Accountability: Explainability ensures accountability in machine learning and AI systems. References Castillo, D.

Machine Learning 52

Machine Learning Explainability Deep Learning Explainable AI 52

Pickl AI

DECEMBER 10, 2024

Summary : Data Analytics trends like generative AI, edge computing, and Explainable AI redefine insights and decision-making. Businesses harness these innovations for real-time analytics, operational efficiency, and data democratisation, ensuring competitiveness in 2025.

Explainable AI 52

Explainable AI Explainability ETL Automation 52

Pickl AI

JULY 14, 2023

The following blog will emphasise on what the future of AI looks like in the next 5 years. Evolution of AI The evolution of Artificial Intelligence (AI) spans several decades and has witnessed significant advancements in theory, algorithms, and applications.

Neural Network 52

Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

ODSC - Open Data Science

FEBRUARY 18, 2025

AI Explainability Specialists: As AI models become increasingly complex, understanding their decision-making processes is crucial. AI explainability specialists develop techniques and tools to interpret and explain AI outputs, fostering trust and transparency.

Explainability 59

Explainability Automation AI AI 59

Defined.ai blog

AUGUST 10, 2023

AI refers to computer systems capable of executing tasks that typically require human intelligence. On the other hand, ML, a subset of AI, involves algorithms that improve through experience. These algorithms learn from data, making the software more efficient and accurate in predicting outcomes without explicit programming.

Business Intelligence 52

Business Intelligence Data Analysis Neural Network Data Quality 52

Pickl AI

JANUARY 13, 2025

With clear and engaging writing, it covers a range of topics, from basic AI principles to advanced concepts. Readers will gain a solid foundation in search algorithms, game theory, multi-agent systems, and more. Key Features: Comprehensive coverage of AI fundamentals and advanced topics. Detailed algorithms and pseudo-codes.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Neural Network Machine Learning 52

Bugra Akyildiz

MAY 25, 2024

There are also a variety of capabilities that can be very useful for ML/Data Science Practitioners for data related or feature related tasks. Data Tasks ChatGPT can handle a wide range of data-related tasks by writing and executing Python code behind the scenes, without users needing coding expertise.

ChatGPT 59

ChatGPT Machine Learning Data Analysis OpenAI 59

ODSC - Open Data Science

FEBRUARY 25, 2025

This track is designed to help practitioners strengthen their ML foundations while exploring advanced algorithms and deployment techniques.

Data Scientist 52

Data Scientist Machine Learning Large Language Models ML Engineer 52

Pickl AI

AUGUST 14, 2024

Fundamentals of Machine Learning Machine Learning is a subset of Artificial Intelligence that focuses on developing algorithms that allow computers to learn from and make predictions based on data. Unsupervised Learning : The model is trained on data without explicit labels, aiming to identify patterns or groupings within the data.

Neural Network 52

Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 52

AWS Machine Learning Blog

NOVEMBER 9, 2023

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance.

Data Drift 118

Data Drift Auto-complete ML Automation 118

Heartbeat

FEBRUARY 2, 2024

As AI strives to emulate human-like understanding, VQA plays a pivotal role by demanding systems to recognize objects and scenes in images and comprehend and respond to human-generated questions about those images. It's remarkable diversity and scale position it as a cornerstone for evaluating and benchmarking VQA algorithms.

Computer Vision 52

Computer Vision Natural Language Processing Artificial Intelligence Artificial Intelligence 52

Heartbeat

SEPTEMBER 7, 2023

Imagine an AI system deciding whether a loan application is approved or denied. Without the ability to explain why a particular decision was made, the applicant might feel an inscrutable algorithm determines their fate. This lack of transparency can lead to mistrust and even legal and ethical concerns.

Explainability 52

Explainability Machine Learning Data Scientist Deep Learning 52

Heartbeat

NOVEMBER 27, 2023

Deep learning algorithms can accurately detect lung cancer nodules in CT scans, diabetic retinopathy in retinal pictures, and breast cancer in mammograms. Explainable AI and Interpretability The decision-making process of deep learning models is unintelligible and inexplicable, making medical picture interpretation difficult.

Deep Learning 59

Deep Learning Convolutional Neural Networks Neural Network Explainability 59

Viso.ai

MAY 10, 2024

It can also help reduce the dimensionality of the input which can help to avoid overfitting in situations where we don’t have as much training data as we would like. It often helps to do some exploratory data science. Try running some basic statistical analyses on your data. How do we perform feature engineering?

Machine Learning 52

Machine Learning Computer Vision Neural Network Convolutional Neural Networks 52

Unite.AI

MARCH 5, 2025

Jamie Twiss is an experienced banker and a data scientist who works at the intersection of data science, artificial intelligence, and consumer lending. He currently serves as the Chief Executive Officer of Carrington Labs , a leading provider of explainable AI-powered credit risk scoring and lending solutions.

Explainability 147

Explainability Big Data AI Modeling Automation 147

Pickl AI

APRIL 2, 2024

Summary This blog post demystifies data science for business leaders. It explains key concepts, explores applications for business growth, and outlines steps to prepare your organization for data-driven success. Data Science Cheat Sheet for Business Leaders In today’s data-driven world, information is power.

Data Science 52

Data Science Data Scientist Machine Learning Big Data 52

Pickl AI

MAY 15, 2024

Dreaming of a Data Science career but started as an Analyst? This guide unlocks the path from Data Analyst to Data Scientist Architect. So if you are looking forward to a Data Science career , this blog will work as a guiding light.

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Data Scientist Data Science Machine Learning Data Quality 52