ODSC - Open Data Science

NOVEMBER 30, 2023

Healthcare systems are implementing AI, and patients and clinicians want to know how it works in detail. Explainable AI might be the solution everyone needs to develop a healthier, more trusting relationship with technology while expediting essential medical care in a highly demanding world. What Is Explainable AI?

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Towards AI

OCTOBER 19, 2024

Yet, for all their sophistication, they often can’t explain their choices — this lack of transparency isn’t just frustrating — it’s increasingly problematic as AI becomes more integrated into critical areas of our lives. What is Explainability AI (XAI)? It’s particularly useful in natural language processing [3].

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IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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Towards AI

NOVEMBER 1, 2023

Last Updated on November 2, 2023 by Editorial Team Author(s): Ahmed Fessi Originally published on Towards AI.

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IBM Journey to AI blog

AUGUST 11, 2023

Today, 35% of companies report using AI in their business, which includes ML, and an additional 42% reported they are exploring AI, according to the IBM Global AI Adoption Index 2022. MLOps is the next evolution of data analysis and deep learning. Looking to scale the impact of AI across your business?

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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.

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Pickl AI

OCTOBER 8, 2024

Summary: This blog discusses Explainable Artificial Intelligence (XAI) and its critical role in fostering trust in AI systems. One of the most effective ways to build this trust is through Explainable Artificial Intelligence (XAI). What is Explainable AI (XAI)? What is Explainable AI (XAI)?

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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. Explainability is essential for accountability, fairness, and user confidence.

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AI Weekly

OCTOBER 3, 2024

radiologybusiness.com Research How cold hard data science harnesses AI with Wolfram Research It’s sometimes difficult to distinguish the reality of technology from the hype and marketing messages that bombard our inboxes daily.

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Towards AI

MAY 6, 2024

A typical SHAP Plot — Image by Author In Part 1 of Data Science Case Study — Credit Default Prediction, we have talked about feature engineering, model training, model evaluation and classification threshold selection. Model Explainability Our model can make predictions by feeding into it the features. Let’s jump in!

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Pickl AI

JULY 1, 2024

Demand forecasting, powered by data science, helps predict customer needs. Optimize inventory, streamline operations, and make data-driven decisions for success. Data Science empowers businesses to leverage the power of data for accurate and insightful demand forecasts.

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Heartbeat

SEPTEMBER 13, 2023

Source: ResearchGate Explainability refers to the ability to understand and evaluate the decisions and reasoning underlying the predictions from AI models (Castillo, 2021). Explainability techniques aim to reveal the inner workings of AI systems by offering insights into their predictions. What is Explainability?

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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.

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IBM Journey to AI blog

MAY 9, 2023

Success in delivering scalable enterprise AI necessitates the use of tools and processes that are specifically made for building, deploying, monitoring and retraining AI models. Consistent principles guiding the design, development, deployment and monitoring of models are critical in driving responsible, transparent and explainable AI.

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Heartbeat

SEPTEMBER 7, 2023

In the ever-evolving landscape of machine learning and artificial intelligence, understanding and explaining the decisions made by models have become paramount. Enter Comet , that streamlines the model development process and strongly emphasizes model interpretability and explainability. Why Does It Matter?

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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. Your customers deserve and are holding your organization accountable to explain reasons for analytics-based decisions.

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Mlearning.ai

JANUARY 26, 2023

When it comes to implementing any ML model, the most difficult question asked is how do you explain it. Suppose, you are a data scientist working closely with stakeholders or customers, even explaining the model performance and feature selection of a Deep learning model is quite a task. How can we explain it in simple terms?

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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. Let us go further into the enigmas of Artificial Intelligence, where AI is making waves like never before! So, don’t worry, this is where Explainable AI, also known as XAI, comes in.

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IBM Journey to AI blog

OCTOBER 16, 2023

Foundation models are widely used for ML tasks like classification and entity extraction, as well as generative AI tasks such as translation, summarization and creating realistic content. The development and use of these models explain the enormous amount of recent AI breakthroughs. Increase trust in AI outcomes.

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ODSC - Open Data Science

DECEMBER 7, 2023

8 Tools to Protect Sensitive Data from Unintended Leakage In order to protect themselves from unintended leakage of sensitive information, organizations employ a variety of tools that scan repositories and code continuously to identify the secrets that are hard-coded within. Use our guide to help you ask the right questions to get you in.

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ODSC - Open Data Science

JUNE 7, 2023

Interactive Explainable AI Meg Kurdziolek, PhD | Staff UX Researcher | Intrinsic.ai Although current explainable AI techniques have made significant progress toward enabling end-users to understand the why behind a prediction, to effectively build trust with an AI system we need to take the next step and make XAI tools interactive.

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ODSC - Open Data Science

SEPTEMBER 26, 2024

The NVIDIA AI Hackathon at ODSC West, Reinforcement Learning for Finance, the Future of Humanoid AI Robotics, and Detecting Anomalies Unleash Innovation at the NVIDIA AI Hackathon at ODSC West 2024 Ready to put your data science skills to the test? Where do explainable AI models come into play?

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ODSC - Open Data Science

OCTOBER 21, 2024

From model fairness to explainability, TensorFlow provides extensive tools and documentation to ensure AI systems are ethically sound and free from bias. And this platform reflects its commitment to developing and deploying AI systems that are fair, transparent, and accountable.

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ODSC - Open Data Science

FEBRUARY 27, 2024

Interactive Explainable AI Meg Kurdziolek, PhD | Staff UX Researcher | Intrinsic.ai Although current explainable AI techniques have made significant progress toward enabling end-users to understand the why behind a prediction, to effectively build trust with an AI system we need to take the next step and make XAI tools interactive.

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ODSC - Open Data Science

AUGUST 14, 2023

“I still don’t know what AI is” If you’re like my parents and think I work at ChatGPT, then you may have to learn a little bit more about AI. Funny enough, you can use AI to explain AI. Most AI-based programs have plenty of good tutorials that explain how to use the automation side of things as well.

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DataRobot Blog

DECEMBER 6, 2022

Savvy data scientists are already applying artificial intelligence and machine learning to accelerate the scope and scale of data-driven decisions in strategic organizations. These data science teams are seeing tremendous results—millions of dollars saved, new customers acquired, and new innovations that create a competitive advantage.

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Towards AI

AUGUST 31, 2023

Last Updated on September 1, 2023 by Editorial Team Author(s): Louis Bouchard Originally published on Towards AI. An introduction to explainable AI This member-only story is on us. Often called hallucinations, these problems can be harmful, especially if we blindly trust the AI. Upgrade to access all of Medium.

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Towards AI

FEBRUARY 22, 2024

Our friends at Zoī are hiring their Chief AI Officer. Zoī is at the crossroads of 3 domains: Medical, Data Science, and BeSci. Zoī aims to create personalized user manuals for each member by gathering only the necessary data to provide tailored recommendations based on thousands of factors. Our must-read articles 1.

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ODSC - Open Data Science

FEBRUARY 13, 2023

Explainable AI: As in the namesake, explainable AI’s purpose is to clearly and in a transparent manner, explain why a machine learning model came to a specific decision. First are two techniques that tackle the question of why predictions are made and explain them. Here are a few that are raising eyebrows.

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IBM Journey to AI blog

MARCH 7, 2023

This required a model with a high level of precision that also is built upon key principles of trustworthy AI including transparency, explainability, fairness, privacy and robustness. The Innocens team needed to build a model that could detect subtle changes in neonates’ vital signs while generating as few false alarms as possible.

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ODSC - Open Data Science

OCTOBER 24, 2023

Figure 1: Synthetic data (left) versus real (right), Telecom dataset The main hyperparameter vector specifies the number of quantile intervals to use for each feature (one per feature). Indeed, the whole technique epitomizes explainable AI. It is easy to fine-tune, allowing for auto-tuning.

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ODSC - Open Data Science

OCTOBER 10, 2024

As part of our efforts to grow the data science community, we are offering our support to startups in these fields to help them spread the word to VCs, conference audiences, and the data science community.

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NYU Center for Data Science

JUNE 16, 2023

Motivated by applications in healthcare and criminal justice, Umang studies how to create algorithmic decision-making systems endowed with the ability to explain their behavior and adapt to a stakeholder’s expertise to improve human-machine team performance. By Meryl Phair

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ODSC - Open Data Science

FEBRUARY 22, 2024

Andre Franca | CTO | connectedFlow Join this session to demystify the world of Causal AI, with a focus on understanding cause-and-effect relationships within data to drive optimal decisions. By the end, you will be ready to harness the platform for advanced spatial analysis and the development of sophisticated AI models.

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Pickl AI

SEPTEMBER 17, 2024

Obtaining and curating this data can be time-consuming and resource-intensive, and there is always the risk of data bias or imbalance. Additionally, as AI models become more complex and opaque, it can be difficult to explain their decision-making processes, which can be a concern for regulatory compliance and legal liability.

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ODSC - Open Data Science

JUNE 8, 2023

The week was filled with engaging sessions on top topics in data science, innovation in AI, and smiling faces that we haven’t seen in a while. Some of our most popular in-person sessions were: Data Science Software Acceleration at the Edge: Audrey Reznik Guidera | Sr.

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ODSC - Open Data Science

MAY 30, 2023

Within the European COST Action «Fintech and AI in Finance», he leads the working group «Transparency into Investment Product Performance for Clients». Originally posted on OpenDataScience.com Read more data science articles on OpenDataScience.com , including tutorials and guides from beginner to advanced levels!

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