IBM Journey to AI blog

MAY 10, 2024

Underpinning most artificial intelligence (AI) deep learning is a subset of machine learning that uses multi-layered neural networks to simulate the complex decision-making power of the human brain. Deep learning requires a tremendous amount of computing power.

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PyImageSearch

DECEMBER 9, 2024

In the 1st blog of this series , you were introduced to Photogrammetry, which is based on 3D Reconstruction via heavy geometry. And in the 2nd blog of this series , you were introduced to NeRFs, which is 3D Reconstruction via Neural Networks, projecting points in the 3D space. 2023 ) See how we added 3 blocks? Thats A, B, and C.

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Data Science Dojo

JULY 2, 2023

Transformers, a type of Deep Learning model, have played a crucial role in the rise of LLMs. By analyzing diverse data sources and incorporating advanced machine learning algorithms, LLMs enable more informed decision-making, minimizing potential risks.

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PyImageSearch

DECEMBER 23, 2024

These scenarios demand efficient algorithms to process and retrieve relevant data swiftly. This is where Approximate Nearest Neighbor (ANN) search algorithms come into play. ANN algorithms are designed to quickly find data points close to a given query point without necessarily being the absolute closest.

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Data Science Dojo

FEBRUARY 13, 2025

Whether you’re a researcher, developer, startup founder, or simply an AI enthusiast, these events provide an opportunity to learn from the best, gain hands-on experience, and discover the future of AI. Machine Learning & Deep Learning Advances Gain insights into the latest ML models, neural networks, and generative AI applications.

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The MLOps Blog

NOVEMBER 14, 2023

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The reasons for this range from wrongly connected model components to misconfigured optimizers.

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IBM Data Science in Practice

MARCH 21, 2023

In this blog, we go over a use case of an AI assisted image recognition process that consisted of many deep learning models. Aggregation Methods: A single deep learning model produces a matrix of prediction probabilities of each class for each section of the original image. This was a standard WML deployment.

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PyImageSearch

JANUARY 30, 2023

This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector. To learn about Computer Vision and Deep Learning for Education, just keep reading. This series is about CV and DL for Industrial and Big Business Applications.

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Data Science Dojo

MAY 27, 2024

In this blog, we will explore the details of both approaches and navigate through their differences. A visual representation of generative AI – Source: Analytics Vidhya Generative AI is a growing area in machine learning, involving algorithms that create new content on their own. What is Generative AI?

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Towards AI

JANUARY 31, 2025

Explaining a black box Deep learning model is an essential but difficult task for engineers in an AI project. Explainability leverages user interfaces, charts, business intelligence tools, some explanation metrics, and other methodologies to discover how the algorithms reach their conclusions. This member-only story is on us.

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Data Science Dojo

SEPTEMBER 25, 2024

By leveraging AI-powered algorithms, media producers can improve production processes and enhance creativity. In this blog, we will explore the impact of AI on media production, analyzing how it benefits the people working within this industry and the audiences. The advantages of using AI in media production processes are multifaceted.

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Flipboard

JULY 31, 2023

Searching for the best AI blog writer to beef up your content strategy? But in this guide, we’ve curated a list of the top 10 AI blog writers to streamline your content creation. From decoding the complex algorithms to highlighting unique features, this article is your one-stop shop for finding the perfect AI blog writer for you.

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DrivenData Labs

MAY 12, 2025

competition, winning solutions used deep learning approaches from facial recognition tasks (particularly ArcFace and EfficientNet) to help the Bureau of Ocean and Energy Management and NOAA Fisheries monitor endangered populations of beluga whales by matching overhead photos with known individuals. For example: In the Where's Whale-do?

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Google Research AI blog

FEBRUARY 10, 2023

Robust algorithm design is the backbone of systems across Google, particularly for our ML and AI models. Hence, developing algorithms with improved efficiency, performance and speed remains a high priority as it empowers services ranging from Search and Ads to Maps and YouTube. You can find other posts in the series here.)

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Towards AI

NOVEMBER 16, 2024

Keswani’s Algorithm introduces a novel approach to solving two-player non-convex min-max optimization problems, particularly in differentiable sequential games where the sequence of player actions is crucial. Keswani’s Algorithm: The algorithm essentially makes response function : maxy∈{R^m} f (.,

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Data Science Dojo

APRIL 27, 2023

This blog lists down-trending data science, analytics, and engineering GitHub repositories that can help you with learning data science to build your own portfolio.  What is GitHub? It provides a range of algorithms for classification, regression, clustering, and more.  

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AWS Machine Learning Blog

OCTOBER 24, 2024

Alternatives to Rekognition people pathing One alternative to Amazon Rekognition people pathing combines the open source ML model YOLOv9 , which is used for object detection, and the open source ByteTrack algorithm, which is used for multi-object tracking.

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Data Science Dojo

JULY 2, 2024

In this blog, we will focus on one such developed aspect of AI called adaptive AI. It is a form of AI that learns, adapts, and improves as it encounters changes, both in data and the environment. Some key characteristics that make AI adaptive are: Ability to Learn Continuously The AI system can process and analyze new information.

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Data Science Dojo

JUNE 14, 2023

By applying AI algorithms and technologies, manufacturers can automate quality control, predictive maintenance, resource optimization, and other operations, leading to increased efficiency and cost savings 2. If you’re interested in learning more about this exciting technology, I encourage you to check out one of these courses.

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Data Science Dojo

NOVEMBER 18, 2023

Learning about LLMs is essential in today’s fast-changing technological landscape. This blog lists steps and several tutorials that can help you get started with large language models. But what if we could use deep learning to revolutionize search?

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Pickl AI

APRIL 9, 2025

Summary: Artificial Intelligence (AI) and Deep Learning (DL) are often confused. AI vs Deep Learning is a common topic of discussion, as AI encompasses broader intelligent systems, while DL is a subset focused on neural networks. Is Deep Learning just another name for AI? Is all AI Deep Learning?

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PyImageSearch

APRIL 7, 2025

In this blog post, we will understand the concept of SVD and know how it can be used for matrix diagonalization and data compression. Singular Value Decomposition Singular Value Decomposition (SVD) is a popular algorithm used to diagonalize a matrix of an arbitrary shape.

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Pickl AI

DECEMBER 29, 2024

Introduction Mathematics forms the backbone of Artificial Intelligence , driving its algorithms and enabling systems to learn and adapt. Structured for clarity, the blog breaks down complex topics into actionable insights, ensuring a seamless learning journey for readers.

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IBM Data Science in Practice

NOVEMBER 21, 2022

Leverage the Watson NLP library to build the best classification models by combining the power of classic ML, Deep Learning, and Transformed based models. link] Text classification is one of the most used NLP tasks for several use cases like email spam filtering, tagging, and classifying content, blogs, metadata, etc.

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PyImageSearch

OCTOBER 14, 2024

This blog post is the 1st of a 3-part series on 3D Reconstruction: Photogrammetry Explained: From Multi-View Stereo to Structure from Motion (this blog post) 3D Reconstruction: Have NeRFs Removed the Need for Photogrammetry? The second blog post will introduce you to NeRFs , the neural network solution. Then, between 2 and 3.

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Data Science Dojo

JULY 4, 2023

With a foundation in math, statistics, and programming, learning Generative AI requires dedication and patience as the technology evolves. Generative AI harnesses deep learning algorithms to generate human-like data in response to user input. We hope this Generative AI Roadmap blog is helpful.

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AWS Machine Learning Blog

DECEMBER 2, 2024

Over the past decade, advancements in deep learning have spurred a shift toward so-called global models such as DeepAR [3] and PatchTST [4]. AutoGluon predictors can be seamlessly deployed to SageMaker using AutoGluon-Cloud and the official Deep Learning Containers.

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Towards AI

JANUARY 9, 2024

In other words, we all want to get directly into Deep Learning. But this is really a mistake if you want to take studying Machine Learning seriously and get a job in AI. Machine Learning fundamentals are not 100% the same as Deep Learning fundamentals and are perhaps even more important.

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PyImageSearch

APRIL 21, 2025

In this blog post, we will explore the theory behind QR Decomposition and its application in solving the OLS regression problem. Gram-Schmidt Process for QR Factorization The Gram-Schmidt algorithm ( Figure 4 ) is a method for obtaining the QR factorization of a matrix by orthogonalizing its columns. 0.82807867 2.76026224] [ 0.

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NYU Center for Data Science

AUGUST 8, 2023

This entry is a part of our Meet the Fellow blog series, which introduces and highlights Faculty Fellows who have recently joined CDS. In his research, Guth seeks to understand how deep learning manages to exploit the structure of real-world learning problems and work so effectively in practice.

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Data Science Dojo

NOVEMBER 3, 2023

This blog lists several YouTube channels that can help you get started with llms, generative AI, prompt engineering, and more. Large language models, like GPT-3.5, have revolutionized the field of natural language processing.

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Data Science Dojo

NOVEMBER 3, 2023

Understanding their capabilities and limitations empowers individuals and professionals across various fields.   This blog lists several YouTube channels that can help you get started with llms, generative AI, prompt engineering, and more.   Want to delve deeper into large language models?

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Flipboard

MAY 29, 2025

Starting this fall, the Allen School will offer a stackable Graduate Certificate in Modern AI Methods , a part-time evening program aimed at a growing number of professionals across a wide range of industries who need to understand, leverage and integrate AI and machine learning as part of their work.

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PyImageSearch

OCTOBER 28, 2024

In this blog post, you will learn about 3D Reconstruction. One day, I was looking for an email idea while writing my daily self-driving car newsletter , when I was suddenly caught by the news: Tesla had released a new FSD12 model based on End-to-End Learning. And that is the topic of this blog post #2 on NeRFs.

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Towards AI

DECEMBER 28, 2023

Black box algorithms such as xgboost emerged as the preferred solution for a majority of classification and regression problems. The advent of more powerful personal computers paved the way for the gradual acceptance of deep learning-based methods. CS6910/CS7015: Deep Learning Mitesh M.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

Large-scale deep learning has recently produced revolutionary advances in a vast array of fields. is a startup dedicated to the mission of democratizing artificial intelligence technologies through algorithmic and software innovations that fundamentally change the economics of deep learning. and PyTorch 2.0

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DataRobot Blog

APRIL 21, 2022

Machine learning, and especially deep learning, has become increasingly more accurate in the past few years. In the graph below, borrowed from the same article, you can see how some of the most cutting-edge algorithms in deep learning have increased in terms of model size over time.

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