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. This is where model explainability comes into picture. This article is the continuation of Part 1.

Data Science 90

Data Science Explainability Explainable AI Machine Learning 90

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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Data Science ML Machine Learning Artificial Intelligence 52

IBM Journey to AI blog

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. An AI governance framework ensures the ethical, responsible and transparent use of AI and machine learning (ML). ” Are foundation models trustworthy? .

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Metadata Explainability Automation Explainable AI 220

Unite.AI

APRIL 9, 2024

These techniques include Machine Learning (ML), deep learning , Natural Language Processing (NLP) , Computer Vision (CV) , descriptive statistics, and knowledge graphs. Composite AI plays a pivotal role in enhancing interpretability and transparency. Combining diverse AI techniques enables human-like decision-making.

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Composite AI Explainability Neural Network Black Box AI 176

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

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IBM Journey to AI blog

SEPTEMBER 20, 2023

Foundational models (FMs) are marking the beginning of a new era in machine learning (ML) and artificial intelligence (AI) , which is leading to faster development of AI that can be adapted to a wide range of downstream tasks and fine-tuned for an array of applications. IBM watsonx consists of the following: IBM watsonx.ai

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Large Language Models DevOps Data Science AI Modeling 238

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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Explainable AI Data Science Responsible AI Machine Learning 93

ODSC - Open Data Science

FEBRUARY 24, 2023

Its goal is to help with a quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. Apache Superset GitHub | Website Apache Superset is a must-try project for any ML engineer, data scientist, or data analyst.

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Data Analysis Data Science Business Intelligence Python 126

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. sales) and independent variables (e.g.,

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ODSC - Open Data Science

MAY 30, 2023

Be sure to check out his talk, “ ML Applications in Asset Allocation and Portfolio Management ,” there! The year 2022 presented two significant turnarounds for tech: the first one is the immediate public visibility of generative AI due to ChatGPT. Editor’s note: Peter Schwendner, PhD is a speaker for ODSC Europe this June.

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ML Data Science Machine Learning Explainable AI 52

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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Data Scientist Explainable AI Data Science Python 98

ODSC - Open Data Science

OCTOBER 21, 2024

Fortunately, there are many tools for ML evaluation and frameworks designed to support responsible AI development and evaluation. This topic is closely aligned with the Responsible AI track at ODSC West  — an event where experts gather to discuss innovations and challenges in 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)?

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Explainability Explainable AI Natural Language Processing Prompt Engineer 105

The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

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Unite.AI

JUNE 24, 2024

Steven Hillion is the Senior Vice President of Data and AI at Astronomer , where he leverages his extensive academic background in research mathematics and over 15 years of experience in Silicon Valley's machine learning platform development. Can you elaborate on the use of synthetic data to fine-tune smaller models for accuracy?

Data Scientist 130

Data Scientist Large Language Models Machine Learning Software Engineer 130

Mlearning.ai

FEBRUARY 6, 2023

Like issue 1, this could be solved over time through more tailored data sets and training. Classifiers based on neural networks are known to be poorly calibrated outside of their training data [3]. There are plenty of techniques to help reduce overfitting in ML models. This is why we need Explainable AI (XAI).

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Explainable AI Explainability ChatGPT Chatbots 52

ODSC - Open Data Science

JUNE 1, 2023

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East Highlights Getting Up to Speed on Real-Time Machine Learning with Spark and SBERT Learn more about real-time machine learning by using this approach that uses Apache Spark and SBERT. Is an AI Coding Assistant Right For You?

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ML Data Scientist Big Data Data Science 52

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.

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Artificial Intelligence Artificial Intelligence Automation Explainable AI 52

Marktechpost

MAY 12, 2024

Greip Greip is an AI-powered fraud protection tool that assists developers in protecting their app’s financial security by avoiding payment fraud. Greip provides an AI-powered fraud protection solution that utilizes ML modules to validate each transaction in an app and assess the possibility of fraudulent behavior.

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AI Tools Neural Network Artificial Intelligence Artificial Intelligence 102

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. Techniques such as embodied AI, multimodal learning, knowledge graphs, reinforcement learning, and explainable AI are paving the way for more grounded and reliablesystems.

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Robotics Explainable AI Data Scientist Explainability 40

Unite.AI

DECEMBER 1, 2023

I was fascinated by how much human knowledge—anything anyone had ever deemed patentable—was readily available, yet so inaccessible because it was so hard to do even the simplest analysis over complex technical text and multi-modal data. When that’s the case, the best way to improve these models is to supply them with more and better data.

Data Scientist 144

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Towards AI

FEBRUARY 22, 2024

If you’re passionate about ML and interested in collaborative learning, connect in the thread! Our friends at Zoī are hiring their Chief AI Officer. Zoī is at the crossroads of 3 domains: Medical, Data Science, and BeSci. Mh_aghajany is looking for fellow learners to explore Machine Learning, Deep Learning, and LLM.

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Large Language Models Explainability AI AI 111

AWS Machine Learning Blog

APRIL 12, 2023

With “Science of Gaming” as their core philosophy, they have enabled a vision of end-to-end informatics around game dynamics, game platforms, and players by consolidating orthogonal research directions of game AI, game data science, and game user research.

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Metadata Deep Learning ML Data Science 94

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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Robotics Data Science Large Language Models Explainable AI 52

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.

Explainable AI 52

Explainable AI Data Science Responsible AI Machine Learning 52

Marktechpost

AUGUST 24, 2023

Here’s our curated list of the top AI and Machine Learning-related subreddits to follow in 2023 to keep you in the loop. million members, this is a must-join group for ML enthusiasts. r/artificial r/artificial is the largest subreddit dedicated to all issues related to Artificial Intelligence or AI. With over 2.5

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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.

Data Science 52

Data Science Machine Learning NLP Software Engineer 52

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 of this session, you’ll have a practical blueprint to efficiently harness feature stores within ML workflows.

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Machine Learning Data Science Python ML 52

DataRobot Blog

JUNE 23, 2022

Rather than waiting until a prediction has been made, savvy business people are focusing not on what machine learning (ML) techniques might result in an interesting prediction but instead are turning their minds to the question “What do I need to know to change the way we make decisions?”. DATAROBOT AI CLOUD. Macro and Micro Analysis.

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Data Science AI AI ML 59

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.

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Dlabs.ai

MAY 22, 2022

That shows how companies are increasingly investing in ML solutions, often looking for skilled professionals to help them create custom software. Given the data, it’s little surprise that many people want to learn more about AI and ML and, in turn, develop the necessary skills to become a machine learning engineer.

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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.

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Heartbeat

SEPTEMBER 13, 2023

Distinction Between Interpretability and Explainability Interpretability and explainability are interchangeable concepts in machine learning and artificial intelligence because they share a similar goal of explaining AI predictions. Explainability in Machine Learning || Seldon Blazek, P. Russell, C. &

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ODSC - Open Data Science

FEBRUARY 25, 2025

Topics Include: Agentic AI DesignPatterns LLMs & RAG forAgents Agent Architectures &Chaining Evaluating AI Agent Performance Building with LangChain and LlamaIndex Real-World Applications of Autonomous Agents Who Should Attend: Data Scientists, Developers, AI Architects, and ML Engineers seeking to build cutting-edge autonomous systems.

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Data Scientist Machine Learning Large Language Models ML Engineer 52

Mlearning.ai

FEBRUARY 7, 2023

Image Credit: LearnGPT 100+: Many, many plus more coding examples 4x: Aleksander Lütken on daily work automation 3x: Using it to setup an Android app 5x: Tanya Tsui: Writing python code for a geo-data project. 1x: A nice prompt forcing the AI to interrupt itself while explaining AI alignment.

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Pickl AI

JULY 14, 2023

However, symbolic AI faced limitations in handling uncertainty and dealing with large-scale data. Machine Learning and Neural Networks (1990s-2000s): Machine Learning (ML) became a focal point, enabling systems to learn from data and improve performance without explicit programming.

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Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

Defined.ai blog

AUGUST 10, 2023

Now, let’s discover how your business can utilize the potential of artificial intelligence to optimize your financial data. Understanding the AI-ML Connection in Financial Data Analysis Artificial Intelligence and Machine Learning (ML) often come hand in hand when discussing advanced technology.

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