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A podcast about the fundamentals of safe and resilient modeling systems behind the AI that impacts our lives and our businesses.
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HumAIn Podcast - Artificial Intelligence, Data Science, Developer Tools, and Technical Education
David Yakobovitch
David Yakobovitch explores AI for consumers through fireside conversations with industry thought leaders on HumAIn. From Chief Data Scientists and AI Advisors, to Leaders who advance AI for All, the HumAIn Podcast is the channel to release new AI products, to learn about industry trends, and to bridge the gap between humans and machines in the Fourth Industrial Revolution.
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Learn how to build a mission-driven machine learning company from the innovators and entrepreneurs who are leading the way. A weekly show about the intersection of ML and business – particularly startups. We discuss the challenges and best practices for working with data, mitigating bias, dealing with regulatory processes, collaborating across disciplines, recruiting and onboarding, maximizing impact, and more.
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Interviews with scientists and engineers working in Machine Learning and AI, about their journey, insights, and discussion on latest research topics.
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Tune in to hear Amanda Razani and Mike Vizard share valuable insights as they explore the latest in artificial intelligence news, discuss key issues and speculate on the future of AI, LLMs and machine learning.
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51
Machine Learning Archives - Software Engineering Daily
Machine Learning Archives - Software Engineering Daily
Machine learning and data science episodes of Software Engineering Daily.
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Brought to you by Alteryx, Alter Everything is a data science and analytics culture podcast featuring industry experts. With topics like machine learning applications, analytics career paths, and everything in between, Alter Everything is a testament to the importance of data literacy in a world powered by data. To view episode transcripts, leave comments, and connect with guests, visit alteryx.com/podcast
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Emerging and future technologies and the trends that they are linked to will be covered on this podcast. From the more obvious tech like: AI, Robotics, Autonomous Vehicles, and The Metaverse. To less well known disruptors like: Brain-Machine Interfaces, CBDC’s, Internet of Bodies, Smart Dust, Animal Human Chimeras, 4D Printing, Under The Skin Surveillance, Bio Computers and much more. A vision of what the future may hold will be painted to alleviate some of our collective Future Shock so we ...
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A melting pot for all things Artificial Intelligence, including the latest AI News, trends, technologies, reviews, analyses, and more!
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NEJM AI Grand Rounds, hosted by Arjun (Raj) Manrai, Ph.D. and Andrew Beam, Ph.D., features informal conversations with a variety of unique experts exploring the deep issues at the intersection of artificial intelligence, machine learning, and medicine. You’ll learn how AI will change clinical practice and healthcare, how it will impact the patient experience, and about the people who are pushing for innovation. Whether you are an AI researcher or a practicing clinician, these conversations w ...
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Short, simple summaries of machine learning topics, to help you prepare for exams, interviews, reading the latest papers, or just a quick brush up. In less than two minutes, we'll cover the most obscure jargon and complex topics in machine learning. For more details, including small animated presentations, please visit erikpartridge.com. Please do join the conversation on Twitter for corrections, conversations, support and more at #mlbytes
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Welcome to "The AI Chronicles", the podcast that takes you on a journey into the fascinating world of Artificial Intelligence (AI), AGI, GPT-5, GPT-4, Deep Learning, and Machine Learning. In this era of rapid technological advancement, AI has emerged as a transformative force, revolutionizing industries and shaping the way we interact with technology. I'm your host, GPT-5, and I invite you to join me as we delve into the cutting-edge developments, breakthroughs, and ethical implications of A ...
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This is Headroom, an iZotope podcast about audio technology hosted by GRAMMY-nominated professional mastering engineer and educator Jonathan Wyner. Tune in each week for conversations with experts across the audio and music worlds on the impact of audio tech, and exciting new developments.
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Recommender Systems are the most challenging, powerful and ubiquitous area of machine learning and artificial intelligence. This podcast hosts the experts in recommender systems research and application. From understanding what users really want to driving large-scale content discovery - from delivering personalized online experiences to catering to multi-stakeholder goals. Guests from industry and academia share how they tackle these and many more challenges. With Recsperts coming from univ ...
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Welcome to the DataCafé: a special-interest Data Science podcast with Dr Jason Byrne and Dr Jeremy Bradley, interviewing leading data science researchers and domain experts in all things business, stats, maths, science and tech.
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The IQT Podcast explores and offers insight about rapidly evolving technology trends and their impact and contributions to national security. Subscribe to hear from IQT and other thought leaders across a variety of tech domains, including AI and machine learning, biotechnology, autonomous systems, and more. IQT identifies, adapts, and delivers technology solutions from commercial startups to support the national security missions of the U.S. and its allies. Learn more at www.iqt.org.
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Are you fascinated by the world-changing potential of artificial intelligence and big data? Or perhaps a little worried about the ethical implications of these powerful technologies? Join host Kelly Smith, co-host of Geek Girl Soup and lifelong learner in AI, data science, and computer science, as she dives deep into the moral dilemmas surrounding the rise of the machines. On Moral Machine, Kelly sits down with leading experts to explore the promises and perils of AI and data-driven innovati ...
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Over the last decade, concerns about the power and danger of Artificial Intelligence have moved from the fantasy of “Terminator” to reality, and anxieties about killer robots have been joined by many others that are more immediate. Robotic systems threaten a massive disruption of employment and transport, while algorithms fuelled by machine learning on (potentially biased) “big data” increasingly play a role in life-changing decisions, whether financial, legal, or medical. More subtly, AI co ...
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Science in Translation is a podcast from the Northwestern University Clinical and Translational Sciences (NUCATS) Institute. On this show, you’ll hear from NUCATS scientists who are dedicated to accelerating how fast they can move a transformational finding in a lab into a treatment, cure, or solution that will improve human health. You will also discover tools and resources available through NUCATS to catalyze, accelerate, and transform translational science. Funded by the NIH’s National Ce ...
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Superheroes of Science is on a mission to highlight current and exciting science and STEM content. Get your science directly from the experts!
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This podcast provides knowledge sharing for data-driven listeners interested in understanding how data impacts the world in many ways . There are so many aspects to data (i.e. programming, statistics, machine learning, artificial intelligence, data visualizations, and more), but there is also the everyday data side (i.e. social media, money, sex, love, diseases, sports and more). I am touching on each and every one of them in a Dapper kind of way.
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Dynamic Topic Models (DTM): Capturing the Evolution of Themes Over Time
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Dynamic Topic Models (DTM) are an advanced extension of topic modeling techniques designed to analyze and understand how topics in a collection of documents evolve over time. Developed to address the limitations of static topic models like Latent Dirichlet Allocation (LDA), DTMs allow researchers and analysts to track the progression and transforma…
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Business Moves, AI Pros and Cons and GPU Optimization - Techstrong AI - EP28
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Amanda Razani and Mike Vizard discuss recent business news, the pros and cons of AI use, AI at the edge and GPU optimization in today's podcast.By Techstrong Group
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Future of Software Development with LLMs, Advice on Building Tech startups & more | Pritika Mehta
37:31
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Pritika is the co-founder of Butternut AI, a platform that allows the creation of professional websites without hiring web developers. Before butternut, Pritika had entrepreneurship experience building some other products, which later got acquired. Time stamps of the conversation00:00 Highlights01:15 Introduction01:50 Entry point in AI03:04 Motivat…
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165: Community Voices: What Do You Love about Alteryx?
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In this special episode, we dive deep into the heart of the Alteryx Community by bringing you the voices of those who know it best—its users Recorded live at Inspire 2024, we listen through the diverse experiences and insights of Alteryx enthusiasts. Join hosts Nicole Johnson and Joshua Burkhow as they listen to real customer stories, react to firs…
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False Positive Rate (FPR): A Critical Metric for Evaluating Classification Accuracy
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The False Positive Rate (FPR) is a crucial metric used to evaluate the performance of binary classification models. It measures the proportion of negative instances that are incorrectly classified as positive by the model. Understanding FPR is essential for assessing how well a model distinguishes between classes, particularly in applications where…
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Revolutionizing Medicine: Biotech, AI, and Next-Gen Sequencing (With Dr. Jonathan Hill of Wasatch BioLabs) -Ep # 154
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In this episode, We explore the Pivotal role of Biotechnology in Advancing Healthcare, focusing on the latest trends in Next-Generation Sequencing, AI-driven Innovations, and their impact on Diagnostics and Personalized Medicine. About the Episode: Biotechnology is one of the most important fields shaping the future of Human Health, Agriculture, an…
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False Negative Rate (FNR): Understanding Missed Predictions in Classification Models
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The False Negative Rate (FNR) is a critical metric used to evaluate the performance of binary classification models, particularly in applications where failing to identify positive instances can have significant consequences. FNR measures the proportion of actual positive instances that are incorrectly classified as negative by the model. This metr…
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Measuring Biodiversity Using Insects with Mads Fogtmann from Fauna Photonics
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What if technology could be the key to averting a biodiversity crisis? Today, I explore this possibility with Mads Fogtmann, Chief Data Officer of FaunaPhotonics, as we discuss their groundbreaking approach to biodiversity monitoring. I talk with Mads about the looming biodiversity crisis, the innovative solutions his team is developing to address …
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True Positive Rate (TPR): A Key Metric for Assessing Classifier Performance
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The True Positive Rate (TPR), also known as sensitivity or recall, is a fundamental metric used to evaluate the performance of binary classification models. TPR measures the proportion of actual positive instances that are correctly identified by the model, making it crucial for applications where correctly identifying positive cases is essential, …
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True Negative Rate (TNR): A Critical Metric for Evaluating Classifier Performance
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The True Negative Rate (TNR), also known as specificity, is a crucial metric in the evaluation of binary classification models. TNR measures the proportion of actual negative instances that are correctly identified by the model. It is particularly important in applications where accurately identifying negative cases is as critical as identifying po…
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Matthews Correlation Coefficient (MCC): A Robust Metric for Evaluating Binary Classifiers
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The Matthews Correlation Coefficient (MCC) is a comprehensive metric used to evaluate the performance of binary classification models. Named after British biochemist Brian W. Matthews, MCC takes into account true and false positives and negatives, providing a balanced measure even when classes are imbalanced. It is particularly valued for its abili…
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Receiver Operating Characteristic (ROC) Curve: A Key Tool for Evaluating Classification Models
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The Receiver Operating Characteristic (ROC) curve is a fundamental tool used in the evaluation of classification models. It is particularly useful for assessing the performance of binary classifiers by visualizing the trade-offs between true positive rates and false positive rates at various threshold settings. The ROC curve provides a comprehensiv…
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Innovation and Commercialization in Biomedical Research with Lisa Dhar, PhD
24:13
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Correlated Topic Model (CTM): Enhancing Topic Modeling with Correlation Structures
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The Correlated Topic Model (CTM) is an advanced probabilistic model developed to address the limitations of traditional topic modeling techniques like Latent Dirichlet Allocation (LDA). Introduced by David Blei and John Lafferty in 2006, CTM enhances topic modeling by capturing correlations between topics, providing a more nuanced and realistic rep…
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AI Skeptics, Software Intelligence, Deepfakes and More - TechstrongAI - EP27
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Amanda Razani and Mike Vizard discuss the pros and cons of AI implementation, tools and software before talking about deepfakes and more in this podcast. Links Referenced in Podcast: AI Skeptics: https://techstrong.ai/uncategorized/enterprises-are-pushing-ai-to-advance-it-index-report/ https://techstrong.ai/building-with-ai/u-s-business-leaders-bul…
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Tanh (Hyperbolic Tangent): A Widely-Used Activation Function in Neural Networks
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The Tanh (Hyperbolic Tangent), is a widely-used activation function in neural networks. Known for its S-shaped curve, the Tanh function maps any real-valued number to a range between -1 and 1, making it a symmetric function around the origin. This symmetry makes it particularly effective for neural networks, providing both positive and negative out…
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AI in Action: From Machine Learning Interpretability to Cybersecurity with Serg Masís and Nirmal Budhathoki
25:37
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In this DSS Podcast, Anna Anisin welcomes Serg Masís, Climate and Agronomic Data Scientist at Syngenta. Serg, an expert in machine learning interpretability and responsible AI, shares his diverse background and journey into data science. He discusses the challenges of building fair and reliable ML models, emphasizing the importance of interpretabil…
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AI and Remote Team Management (With Glyn Roberts of Vention) - Ep #153
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In this Episode, We explore the management of Globally Distributed Teams, the impact of AI on Team Collaboration, and the Digital Transformation Driven by the Pandemic, highlighting both the Benefits and Challenges of Remote Work, and discussing Tools and Cloud platforms that support these teams. About the Episode Today, we're delving into the Dyna…
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Sigmoid Function: The Key to Smooth, Non-Linear Activation in Neural Networks
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The sigmoid function is a fundamental mathematical function used extensively in machine learning, particularly in the context of neural networks. Its characteristic S-shaped curve makes it ideal for scenarios requiring smooth, non-linear transitions. Core Features of the Sigmoid Function Smooth Non-Linearity: The sigmoid function introduces smooth …
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Optimizing Manufacturing with Berk Birand from Fero Labs
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Manufacturing is a fundamental part of our economy. Unfortunately, a huge swath of the industry is still dependent on outdated methods, adversely impacting our environment. To address these challenges, one company is harnessing the power of AI to transform traditional manufacturing, driving unprecedented efficiency and sustainability in the industr…
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Deep LIME (DLIME): Bringing Interpretability to Deep Learning Models
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Deep LIME (DLIME) is an advanced adaptation of the original LIME (Local Interpretable Model-agnostic Explanations) framework, specifically designed to provide interpretability for deep learning models. As deep learning models become increasingly complex and widely used, understanding their decision-making processes is critical for building trust, e…
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LIME-SUP (LIME for Sequential and Unsupervised Problems): Extending Interpretability to Complex Models
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LIME-SUP, short for Local Interpretable Model-agnostic Explanations for Sequential and Unsupervised Problems, is an advanced extension of the LIME framework. Developed to address the interpretability challenges in sequential and unsupervised machine learning models, LIME-SUP provides insights into how these complex models make predictions and gener…
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SHAP (SHapley Additive exPlanations): Unveiling the Inner Workings of Machine Learning Models
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SHAP, short for SHapley Additive exPlanations, is a unified framework designed to interpret the predictions of machine learning models. Developed by Scott Lundberg and Su-In Lee, SHAP leverages concepts from cooperative game theory, particularly the Shapley value, to provide consistent and robust explanations for model predictions. By attributing e…
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LIME (Local Interpretable Model-agnostic Explanations): Demystifying Machine Learning Models
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LIME, short for Local Interpretable Model-agnostic Explanations, is a technique designed to provide interpretability to complex machine learning models. Developed by researchers Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin, LIME helps understand and trust machine learning models by explaining their predictions. It is model-agnostic, meani…
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GPT-4o: The Next Generation of AI Language Models
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GPT-4o, short for Generative Pre-trained Transformer 4 O, is the latest iteration of OpenAI's groundbreaking series of language models. Building upon the success of its predecessors, GPT-4o brings significant advancements in natural language understanding and generation. This state-of-the-art model continues to push the boundaries of what artificia…
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164: Data Analytics and AI Trends for 2024 and Beyond
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Need to catch up on some data analytics and AI trends? This is the episode for you! To help us catch up on data and AI trends, we are joined by Krishnan Venkata, Chief Client Officer at LatentView. Krishnan discusses adopting AI with the fail-fast method, how to approach solving important business problems, and all things trending in the data analy…
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SimCLR: Simple Framework for Contrastive Learning of Visual Representations
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SimCLR (Simple Framework for Contrastive Learning of Visual Representations) is a pioneering approach in the field of self-supervised learning, designed to leverage large amounts of unlabeled data to learn useful visual representations. Developed by researchers at Google Brain, SimCLR simplifies the process of training deep neural networks without …
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Data-Driven Decisions: Transforming Insurance from the C-Suite Down with Max Cho of Coverage Cat
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Max Cho is the CEO and co-founder of Coverage Cat, a startup revolutionizing the insurance industry through data-driven solutions. With a diverse background in technology and finance, Max has held key positions at industry giants including Google, Two Sigma, and Microsoft. His expertise spans software reliability, quantitative analysis, and consume…
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Exploring the NIST AI Risk Management Framework (RMF) with Patrick Hall
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Join us as we chat with Patrick Hall, Principal Scientist at Hallresearch.ai and Assistant Professor at George Washington University. He shares his insights on the current state of AI, its limitations, and the potential risks associated with it. The conversation also touched on the importance of responsible AI, the role of the National Institute of…
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How AI is Impacting Supply Chain Management (With Pete Grett) - EP #152
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In this Episode, We explore the Impact of AI on Supply Chain Management, Covering the Evolution of Supply Chain Technology, the role of AI before and after Generative Models, and Future Possibilities for AI in Enhancing Efficiency and Resilience in Global logistics. About the Episode: In this episode of our podcast, We dive deep into the transforma…
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Hierarchical Dirichlet Processes (HDP): Uncovering Hidden Structures in Complex Data
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Hierarchical Dirichlet Processes (HDP) are a powerful statistical method used in machine learning and data analysis to uncover hidden structures within complex, high-dimensional data. Developed by Teh, Jordan, Beal, and Blei in 2006, HDP extends the Dirichlet Process (DP) to handle grouped data, making it particularly useful for nonparametric Bayes…
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More Successful IVF with Daniella Gilboa from AIVF
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In this episode of Impact AI, we delve into the transformative impact of AI on in-vitro fertilization (IVF) with Daniella Gilboa, co-founder and CEO of AIVF, a startup that develops AI-powered IVF solutions to help increase the certainty of a successful journey to parenthood. Join me as Daniella shares her mission to democratize fertility care and …
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Clari's AI Survey Results - Techstrong AI - EP26
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Amanda Razani speaks with Julien Sauvage, GVP of marketing at Clari, about the outcome of a recent survey that shows many business leaders are losing out on a large portion of global revenue and plan to use AI to improve their situation.By Techstrong Group
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D3.js: Transforming Data into Dynamic Visualizations
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D3.js (Data-Driven Documents) is a powerful JavaScript library used to create dynamic and interactive data visualizations in web browsers. Developed by Mike Bostock, D3.js leverages modern web standards like HTML, SVG, and CSS, allowing developers to bind data to the Document Object Model (DOM) and apply data-driven transformations to create visual…
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Neural Turing Machine (NTM): Bridging Neural Networks and Classical Computing
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The Neural Turing Machine (NTM) is an advanced neural network architecture that extends the capabilities of traditional neural networks by incorporating an external memory component. Developed by Alex Graves, Greg Wayne, and Ivo Danihelka at DeepMind in 2014, NTMs are designed to mimic the functionality of a Turing machine, enabling them to perform…
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Semantic Analysis: Understanding and Interpreting Meaning in Text
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Semantic Analysis is a critical aspect of natural language processing (NLP) and computational linguistics that focuses on understanding and interpreting the meaning of words, phrases, and sentences in context. By analyzing the semantics, or meaning, of language, semantic analysis aims to bridge the gap between human communication and machine unders…
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Model-Agnostic Meta-Learning (MAML): Accelerating Adaptation in Machine Learning
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Model-Agnostic Meta-Learning (MAML) is a revolutionary framework in the field of machine learning designed to enable models to quickly adapt to new tasks with minimal data. Developed by Chelsea Finn, Pieter Abbeel, and Sergey Levine in 2017, MAML addresses the need for fast and efficient learning across diverse tasks by optimizing for adaptability.…
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Latent Semantic Analysis (LSA): Extracting Hidden Meanings in Text Data
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Latent Semantic Analysis (LSA) is a powerful technique in natural language processing and information retrieval that uncovers the underlying structure in a large corpus of text. Developed in the late 1980s, LSA aims to identify patterns and relationships between words and documents, enabling more effective retrieval, organization, and understanding…
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PyDev is a powerful and feature-rich integrated development environment (IDE) for Python, developed as a plugin for the Eclipse platform. Known for its comprehensive support for Python development, PyDev offers a wide range of tools and functionalities designed to enhance productivity and streamline the coding process for Python developers. Whether…
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AI at the Crossroads: Bias, Diversity, and Scalability with Boshika Tara and Dr. June Andrews
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In this week's DSSPodcast, Anna had a conversation with Boshika Tara, Technical Machine Learning Product Manager at H&M Group. Boshika brings over 7 years of experience in technical product development, engineering, and building large-scale ML systems in NLP and Computer Vision. In this episode, she dives into the critical issue of bias in AI, disc…
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AI and how it is Changing Dining Preferences (With Fisayo Oluwadiya of Resactly) - Ep #151.
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In today's episode, we explore how AI is revolutionizing the food industry by enhancing personalization, refining culinary techniques, and transforming dining experiences through innovative applications and ethical practices. About the Episode: In today's episode, we delve into the fascinating intersection of artificial intelligence and the food in…
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Visual Studio Code (VS Code): The Versatile Code Editor for Modern Development
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Visual Studio Code (VS Code) is a free, open-source code editor developed by Microsoft that has rapidly become one of the most popular tools among developers. Released in 2015, VS Code offers a robust set of features designed to enhance productivity and streamline the development process across various programming languages and platforms. Its flexi…
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AI Hype, Data Hoarding and the Impact of AI on Children - Techstrong AI - EP25
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In today's episode, Amanda Razani and Mike Vizard discuss where AI stands in the Gartner Hype Cycle, the problem with data hoarding, new AWS tools, data governance and how AI is affecting children. Links Referenced in Podcast: Gartner Hype Cycle: https://techstrong.ai/articles/where-ai-stands-on-the-gartner-hype-cycle/ https://techstrong.ai/aiops/a…
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Vision Intelligence Filters with Kit Merker from Plainsight Technologies
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Image-based machine learning is fast becoming an AI staple, and with its new Vision Intelligence Filters, Plainsight Technologies is staking its claim as an industry pioneer. Today, I am joined by Plainsight CEO, Kit Merker, who is here to share all the details behind his company’s latest innovation. Kit begins by explaining what Plainsight does an…
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Latent Dirichlet Allocation (LDA): Uncovering Hidden Structures in Text Data
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Latent Dirichlet Allocation (LDA) is a generative probabilistic model used for topic modeling and discovering hidden structures within large text corpora. Introduced by David Blei, Andrew Ng, and Michael Jordan in 2003, LDA has become one of the most popular techniques for extracting topics from textual data. By modeling each document as a mixture …
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Probabilistic Latent Semantic Analysis (pLSA): Uncovering Hidden Topics in Text Data
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Probabilistic Latent Semantic Analysis (pLSA) is a statistical technique used to analyze co-occurrence data, primarily within text corpora, to discover underlying topics. Developed by Thomas Hofmann in 1999, pLSA provides a probabilistic framework for modeling the relationships between documents and the words they contain. This method enhances the …
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SQLAlchemy: A Powerful Toolkit for SQL and Database Management in Python
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SQLAlchemy is a popular SQL toolkit and Object Relational Mapper (ORM) for Python, designed to simplify the interaction between Python applications and relational databases. Developed by Michael Bayer, SQLAlchemy provides a flexible and efficient way to manage database operations, combining the power of SQL with the convenience of Python. It is wid…
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IntelliJ IDEA: The Ultimate IDE for Modern Java Development
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IntelliJ IDEA is a highly advanced and popular integrated development environment (IDE) developed by JetBrains, tailored for Java programming but also supporting a wide range of other languages and technologies. Known for its powerful features, intuitive user interface, and deep integration with modern development workflows, IntelliJ IDEA is a top …
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