Analytics Vidhya

FEBRUARY 4, 2023

NLP has proven to be […] The post Extracting Medical Information From Clinical Text With NLP appeared first on Analytics Vidhya.

Natural Language Processing 291

Natural Language Processing Artificial Intelligence Artificial Intelligence Data Analysis 291

Pickl AI

APRIL 6, 2025

Summary: Deep Learning vs Neural Network is a common comparison in the field of artificial intelligence, as the two terms are often used interchangeably. Introduction Deep Learning and Neural Networks are like a sports team and its star player. Deep Learning Complexity : Involves multiple layers for advanced AI tasks.

Deep Learning 52

Deep Learning Deep Learning Natural Language Processing Machine Learning 52

Data Science Connect

FEBRUARY 2, 2023

Two of the most widely used subfields of AI are deep learning and machine learning. Understanding the key differences between these two technologies is crucial for making informed decisions about which to use for specific tasks. What is Machine Learning? What is Deep Learning?

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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.

Natural Language Processing 369

Natural Language Processing Deep Learning Deep Learning Predictive Analytics 369

Flipboard

MAY 19, 2025

Sequential cross-sectional images from electron microscopy provide high-resolution intracellular structure information. In this study, the deep learning-based automated segmentation of biological images was explored to enable accurate reconstruction of the 3D structures of cells and organelles.

Deep Learning 112

Deep Learning Deep Learning Algorithm Machine Learning 112

Towards AI

SEPTEMBER 10, 2023

What I’ve learned from the most popular DL course Photo by Sincerely Media on Unsplash I’ve recently finished the Practical Deep Learning Course from Fast.AI. So you definitely can trust his expertise in Machine Learning and Deep Learning. Luckily, there’s a handy tool to pick up Deep Learning Architecture.

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Deep Learning Deep Learning ML ML 124

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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K-nearest Neighbors Algorithm Deep Learning Deep Learning 118

AWS Machine Learning Blog

MAY 15, 2025

The banking industry has long struggled with the inefficiencies associated with repetitive processes such as information extraction, document review, and auditing. To address these inefficiencies, the implementation of advanced information extraction systems is crucial.

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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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Deep Learning Deep Learning Data Scientist Machine Learning 111

Data Science Dojo

SEPTEMBER 8, 2023

We’ll dive into the core concepts of AI, with a special focus on Machine Learning and Deep Learning, highlighting their essential distinctions. AI provides engineers with a powerful toolset to make more informed decisions and enhance their interactions with the digital world.

Predictive Analytics 243

Predictive Analytics Analytics Analytics Deep Learning 243

Dataconomy

MARCH 11, 2025

The concept of a target function is an essential building block in the realm of machine learning, influencing how algorithms interpret data and make predictions. It is the mechanism that algorithms strive to approximate as they learn from provided data. Input (I): The data fed into the algorithm for analysis.

Machine Learning 91

Machine Learning Machine Learning Deep Learning Deep Learning 91

Data Science Dojo

FEBRUARY 13, 2025

The notable features of the IEEE conference are: Cutting-Edge AI Research & Innovations Gain exclusive insights into the latest breakthroughs in artificial intelligence, including advancements in deep learning, NLP, and AI-driven automation.

Big Data 294

Big Data Big Data AI AI 294

PyImageSearch

DECEMBER 9, 2024

Citation Information 3D Gaussian Splatting vs NeRF: The End Game of 3D Reconstruction? In this tutorial, you will learn about 3D Gaussian Splatting. Essentially, you send 30+ input images to an SfM algorithm, and it returns a point cloud. 2023 ) See how we added 3 blocks? Thats A, B, and C. So, where do we begin?

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Deep Learning Deep Learning Algorithm Computer Science 116

Data Science Dojo

OCTOBER 31, 2024

For instance, Berkeley’s Division of Data Science and Information points out that entry level data science jobs remote in healthcare involves skills in NLP (Natural Language Processing) for patient and genomic data analysis, whereas remote data science jobs in finance leans more on skills in risk modeling and quantitative analysis.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

Dataconomy

MARCH 21, 2025

Definition and significance of NLP Natural Language Processing is a subset of AI that combines computational linguistics and advanced algorithms to facilitate human-computer interaction. Rule-based systems utilize predefined linguistic rules to analyze text, while machine learning systems rely on data-driven approaches to train models.

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Natural Language Processing Deep Learning Deep Learning Machine Learning 103

Analytics Vidhya

JANUARY 16, 2024

It’s an information titan, handling billions of queries daily, with a user base that spans across the globe. Its algorithm, founded on keyword matching and user behavior analysis, has established the benchmark for swift […] The post Perplexity AI is going to change the way we search, Beware Google!

Algorithm 318

Algorithm AI AI Analytics 318

Towards AI

NOVEMBER 19, 2023

Photo by Pietro Jeng on Unsplash Deep learning is a type of machine learning that utilizes layered neural networks to help computers learn from large amounts of data in an automated way, much like humans do. Loss functions guide learning by measuring errors. Activation functions introduce non-linear patterns.

Deep Learning 126

Deep Learning Deep Learning Natural Language Processing Predictive Analytics 126

Data Science Dojo

SEPTEMBER 25, 2024

By leveraging AI-powered algorithms, media producers can improve production processes and enhance creativity. Some key benefits of integrating the production process with AI are as follows: Personalization AI algorithms can analyze user data to offer personalized recommendations for movies, TV shows, and music.

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AI AI Algorithm Artificial Intelligence 448

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?

Algorithm 130

Algorithm Machine Learning Machine Learning Deep Learning 130

Data Science Dojo

MAY 27, 2024

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. These algorithms use existing data like text, images, and audio to generate content that looks like it comes from the real world.

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K-nearest Neighbors Supervised Learning AI AI 338

Dataconomy

FEBRUARY 20, 2025

This is the goal behind Neurosymbolic AI , a new approach that merges deep learning with coherence-driven inference (CDI). By developing an algorithm that transforms natural language propositions into structured coherence graphs, the researchers benchmark AI models’ ability to reconstruct logical relationships.

AI 121

AI AI Algorithm Computer Science 121

PyImageSearch

JANUARY 20, 2025

This algorithm takes advantage of the frequency of occurrence of each data item (e.g., This results in a significant reduction in the overall size of the data without any loss of information, making Huffman encoding an essential tool in the realm of data compression. Figure 1: Lossy vs. Lossless Compression (source: Imagify ).

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Deep Learning Deep Learning Algorithm Computer Science 113

Dataconomy

MARCH 4, 2025

By creating artificial datasets that mimic real-world statistics without compromising personal information, organizations can harness the power of data while adhering to stringent privacy regulations. Synthetic data is revolutionizing the way we approach data privacy and analysis across various industries. What is synthetic data?

Decision Trees 91

Decision Trees Machine Learning Machine Learning Deep Learning 91

Dataconomy

FEBRUARY 26, 2025

These systems leverage extensive knowledge databases to provide informed recommendations and solutions. Machine learning Machine learning involves analyzing data to develop algorithms that enhance over time. This self-improvement allows machines to make increasingly accurate decisions as they assimilate new information.

Machine Learning 103

Machine Learning Machine Learning Deep Learning Deep Learning 103

Dataconomy

APRIL 21, 2025

Named entity recognition (NER) has emerged as a pivotal component in extracting structured information from unstructured text. Purpose of NER NER plays a crucial role in automated information extraction, dramatically speeding up the analysis of text. Understanding its purpose clarifies why NER is so valuable in data analysis.

Machine Learning 91

Machine Learning Machine Learning Deep Learning Deep Learning 91

Data Science Dojo

MAY 24, 2024

They work at the intersection of various technical domains, requiring a blend of skills to handle data processing, algorithm development, system design, and implementation. Machine Learning Algorithms Recent improvements in machine learning algorithms have significantly enhanced their efficiency and accuracy.

Deep Learning 195

Deep Learning Machine Learning Machine Learning Deep Learning 195

Dataconomy

APRIL 21, 2025

Algorithm development: NLP can utilize rule-based systems, relying on established linguistic rules, or machine learning-based systems, which adapt and learn from training datasets. Current approaches Modern NLP has seen a notable shift toward deep learning techniques and the use of large datasets.

Natural Language Processing 91

Natural Language Processing Deep Learning Deep Learning Computer Science 91

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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Algorithm ML ML AI 103

Dataconomy

FEBRUARY 6, 2024

This popularity is primarily due to the spread of big data and advancements in algorithms. Going back from the times when AI was merely associated with futuristic visions to today’s reality, where ML algorithms seamlessly navigate our daily lives. These technologies have undergone a profound evolution. billion by 2032.

ML 121

ML ML Machine Learning Machine Learning 121

Data Science Dojo

JULY 2, 2024

It is a form of AI that learns, adapts, and improves as it encounters changes, both in data and the environment. Unlike traditional AI, which follows set rules and algorithms and tends to fall apart when faced with obstacles, adaptive AI systems can modify their behavior based on their experiences. What is Adaptive AI?

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AI AI Algorithm Machine Learning 195

Dataconomy

APRIL 25, 2023

By using a set of predefined rules to process information and provide solutions, these systems have become an essential tool for solving complex problems in various fields, from healthcare and finance to manufacturing and logistics. Other approaches include machine learning, deep learning, and natural language processing.

Natural Language Processing 172

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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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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.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Algorithm Machine Learning 52

Dataconomy

MAY 29, 2023

In their quest for effectiveness and well-informed decision-making, businesses continually search for new ways to collect information. QR codes can contain a huge amount of information, such as text, URLs, contact details, and more. In the realm of AI and ML, QR codes find diverse applications across various domains.

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Predictive Analytics ML ML Analytics 208

Hacker News

DECEMBER 4, 2023

Foundation models, now powering most of the exciting applications in deep learning, are almost universally based on the Transformer architecture and its core attention module. Second, even though this change prevents the use of efficient convolutions, we design a hardware-aware parallel algorithm in recurrent mode.

Deep Learning 182

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Dataconomy

APRIL 29, 2025

Overview of classification in machine learning Classification serves as a foundational method in machine learning, where algorithms are trained on labeled datasets to make predictions. Classification methods are vital for organizing information and making data-driven decisions.

Support Vector Machines 91

Support Vector Machines Machine Learning Machine Learning Algorithm 91

Dataconomy

MARCH 17, 2025

Noisy data Noisy data, filled with random variations and irrelevant information, can mislead the model. Model simplification Starting with simpler algorithms can significantly reduce the risk of overfitting. Such models tend to memorize the training data instead of finding the underlying patterns that would allow them to generalize.

Machine Learning 103

Machine Learning Machine Learning Cross Validation Deep Learning 103