Marktechpost

FEBRUARY 15, 2025

Quantization is a crucial technique in deep learning for reducing computational costs and improving model efficiency. Also,feel free to follow us on Twitter and dont forget to join our 75k+ ML SubReddit.

Deep Learning 97

Deep Learning Conversational AI LLM ML 97

Analytics Vidhya

MAY 1, 2023

While this debate continues in the chorus, PwC’s global AI study says that the global economy will see a boost of 14% in GDP […] The post Emerging Trends in AI and ML in 2023 & Beyond appeared first on Analytics Vidhya.

ML 328

ML Artificial Intelligence Artificial Intelligence Machine Learning 328

Analytics Vidhya

JULY 7, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Difference between AI, ML, and DL Everyone wants to become a. The post AI VS ML VS DL-Let’s Understand The Difference appeared first on Analytics Vidhya.

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ML Data Science AI AI 291

AI News

JULY 28, 2023

According to a recent report by Harnham , a leading data and analytics recruitment agency in the UK, the demand for ML engineering roles has been steadily rising over the past few years. Advancements in AI and ML are transforming the landscape and creating exciting new job opportunities.

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ML Data Science ML Engineer Big Data 245

Analytics Vidhya

FEBRUARY 28, 2024

Thanks to the innovative platform Runway ML, this captivating feat is now within reach.

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ML Deep Learning Artificial Intelligence Artificial Intelligence 290

Analytics Vidhya

OCTOBER 17, 2022

Where is Optimization used in DS/ML/DL? The post Optimization Essentials for Machine Learning appeared first on Analytics Vidhya. What are Convex […].

Machine Learning 360

Machine Learning Deep Learning Data Science ML 360

AWS Machine Learning Blog

DECEMBER 12, 2024

The new SDK is designed with a tiered user experience in mind, where the new lower-level SDK ( SageMaker Core ) provides access to full breadth of SageMaker features and configurations, allowing for greater flexibility and control for ML engineers. This is usually achieved by providing the right set of parameters when using an Estimator.

ML 100

ML Python Data Scientist Natural Language Processing 100

IBM Journey to AI blog

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. Machine learning is a subset of AI. This blog post will clarify some of the ambiguity.

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Neural Network Deep Learning Machine Learning Artificial Intelligence 178

Unite.AI

DECEMBER 17, 2024

With higher-quality data and refinements in ML, computer vision, deep learning, and innovative robotics, AI is actively helping growers make agriculture a more viable business endeavor, more sustainable, and more efficient overall. To help aging and short-staffed growers, AI and robotics are becoming ever more common across U.S.

Computer Vision 289

Computer Vision Robotics AI AI 289

The MLOps Blog

MARCH 13, 2025

In our paper Bayesian Deep Learning is Needed in the Age of Large-Scale AI , we argue that the case above is not the exception but rather the rule and a direct consequence of the research community’s focus on predictive accuracy as a single metric of interest. we might not know how fast the parade moves).

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Deep Learning Neural Network Machine Learning Algorithm 59

Analytics Vidhya

JUNE 20, 2024

Introduction An introduction to machine learning (ML) or deep learning (DL) involves understanding two basic concepts: parameters and hyperparameters. When I came across these terms for the first time, I was confused because they were new to me. If you’re reading this, I assume you are in a similar situation too.

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Deep Learning Machine Learning ML 318

Marktechpost

FEBRUARY 9, 2025

Dont Forget to join our 75k+ ML SubReddit. Also,dont forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

Deep Learning 96

Deep Learning Neural Network Conversational AI AI 96

Marktechpost

MARCH 8, 2025

Deep learning models, having revolutionized areas of computer vision and natural language processing, become less efficient as they increase in complexity and are bound more by memory bandwidth than pure processing power. A primary issue in deep learning computation is optimizing data movement within GPU architectures.

Deep Learning 51

Deep Learning Natural Language Processing Computer Vision Algorithm 51

Unite.AI

JANUARY 24, 2025

Claudionor Coelho is the Chief AI Officer at Zscaler, responsible for leading his team to find new ways to protect data, devices, and users through state-of-the-art applied Machine Learning (ML), Deep Learning and Generative AI techniques. He also held ML and deep learning roles at Google.

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Deep Learning Generative AI AI AI 246

Analytics Vidhya

FEBRUARY 16, 2023

Anomaly detection can assist in seeing surges in partially completed or fully completed transactions in sectors like e-commerce, marketing, and others, allowing for aligning to shifts in demand or spotting […] The post Anomaly Detection in ECG Signals: Identifying Abnormal Heart Patterns Using Deep Learning appeared first on Analytics Vidhya. (..)

Deep Learning 178

Deep Learning Computer Vision ML Data Science 178

Analytics Vidhya

DECEMBER 14, 2023

Introduction In the era of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL), the demand for formidable computational resources has reached a fever pitch. This digital revolution has propelled us into uncharted territories, where data-driven insights hold the keys to innovation.

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Deep Learning Artificial Intelligence Artificial Intelligence Machine Learning 319

AI News

JUNE 3, 2024

Harnessing the Power of Machine Learning and Deep Learning At TickLab, our innovative approach is deeply rooted in the advanced capabilities of machine learning (ML) and deep learning (DL). Deep learning, a subset of ML, plays a crucial role in our data analysis and decision-making processes.

Deep Learning 302

Deep Learning Artificial Intelligence Artificial Intelligence Machine Learning 302

Analytics Vidhya

FEBRUARY 21, 2022

Image designed by the author – Shanthababu Introduction Every ML Engineer and Data Scientist must understand the significance of “Hyperparameter Tuning (HPs-T)” while selecting your right machine/deep learning model and improving the performance of the model(s). Make it simple, for every […].

ML Engineer 337

ML Engineer Data Scientist Deep Learning Data Science 337

Marktechpost

APRIL 6, 2024

In deep learning, a unifying framework to design neural network architectures has been a challenge and a focal point of recent research. By applying category theory, the research captures the constraints used in Geometric Deep Learning (GDL) and extends beyond to a wider array of neural network architectures.

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Neural Network Deep Learning ML AI 139

Analytics Vidhya

MARCH 13, 2023

Introduction Deep Learning has revolutionized the field of AI by enabling machines to learn and improve from large amounts of data. This article will […] The post Mediapipe Tasks API and its Implementation in Projects appeared first on Analytics Vidhya.

Deep Learning 290

Deep Learning ML AI AI 290

Unite.AI

FEBRUARY 6, 2025

Their extensive experience in deep learning models and large-scale infrastructure management led to the development of a state-of-the-art platform as a service (PaaS), built to eliminate AI deployment bottlenecks and streamline machine learning workflows.

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DevOps Machine Learning Large Language Models Automation 179

Marktechpost

MAY 2, 2024

Multi-layer perceptrons (MLPs), or fully-connected feedforward neural networks, are fundamental in deep learning, serving as default models for approximating nonlinear functions. The study contributes by expanding the network to arbitrary sizes and depths, making it relevant in modern deep learning.

Deep Learning 138

Deep Learning Neural Network Continuous Learning ML 138

Unite.AI

AUGUST 28, 2024

Deep Instinct is a cybersecurity company that applies deep learning to cybersecurity. As I learned about the possibilities of predictive prevention technology, I quickly realized that Deep Instinct was the real deal and doing something unique. ML is unfit for the task. He holds a B.Sc Not all AI is equal.

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Deep Learning Explainability Neural Network Metadata 278

Marktechpost

MARCH 23, 2024

AI researchers are taking the game to a new level with geometric deep learning. At its core, TacticAI relies on a cutting-edge geometric deep learning pipeline to turn raw football data into structured inputs for AI models to understand. Check out the Paper and Blog. Also, don’t forget to follow us on Twitter.

Deep Learning 144

Deep Learning Neural Network Data Mining Artificial Intelligence 144

Unite.AI

MARCH 15, 2024

Nevertheless, addressing the cost-effectiveness of ML models for business is something companies have to do now. For businesses beyond the realms of big tech, developing cost-efficient ML models is more than just a business process — it's a vital survival strategy. Challenging Nvidia, with its nearly $1.5

ML 188

ML Deep Learning Neural Network Machine Learning 188

ODSC - Open Data Science

MARCH 12, 2025

As a machine learning (ML) practitioner, youve probably encountered the inevitable request: Can we do something with AI? Stephanie Kirmer, Senior Machine Learning Engineer at DataGrail, addresses this challenge in her talk, Just Do Something with AI: Bridging the Business Communication Gap for ML Practitioners.

ML 52

ML Machine Learning AI AI 52

Analytics Vidhya

APRIL 26, 2022

Introduction on Binary Classification Artificial Intelligence, Machine Learning and Deep Learning are transforming various domains and industries. ML is used in healthcare for a variety of purposes. This article was published as a part of the Data Science Blogathon. One such domain is the field of Healthcare.

Deep Learning 271

Deep Learning Artificial Intelligence Artificial Intelligence Machine Learning 271

Marktechpost

NOVEMBER 17, 2024

While deep learning models have achieved state-of-the-art results in this area, they require large amounts of labeled data, which is costly and time-consuming. Active learning helps optimize this process by selecting the most informative unlabeled samples for annotation, reducing the labeling effort.

Deep Learning 99

Deep Learning BERT Automation ML 99

Analytics Vidhya

AUGUST 10, 2023

Introduction In today’s evolving landscape, organizations are rapidly scaling their teams to harness the potential of AI, deep learning, and ML. What started as a modest concept, machine learning, has now become indispensable across industries, enabling businesses to tap into unprecedented opportunities.

Machine Learning 271

Machine Learning Deep Learning ML AI 271

Towards AI

JANUARY 29, 2025

Generative AI is powered by advanced machine learning techniques, particularly deep learning and neural networks, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). Programming Languages: Python (most widely used in AI/ML) R, Java, or C++ (optional but useful) 2.

AI Engineer 98

AI Engineer Generative AI Neural Network BERT 98

Marktechpost

MARCH 5, 2024

Deep Learning models have revolutionized our ability to process and understand vast amounts of data. However, a vast portion of the digital world comprises binary data, the fundamental building block of all digital information, which still needs to be explored by current deep-learning models.

Deep Learning 144

Deep Learning Categorization Algorithm AI 144

Marktechpost

MAY 15, 2024

In contrast, the proposed method, MatterSim, leverages deep learning techniques to understand atomic interactions from the fundamental principles of quantum mechanics. MatterSim is trained on large synthetic datasets that are created by combining active learning, generative models, and molecular dynamics simulations.

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Deep Learning Machine Learning ML Generative AI 128

Marktechpost

MAY 21, 2024

In conclusion, DynamicBind integrates protein conformation generation and ligand pose prediction into a single, end-to-end deep learning framework, significantly faster than traditional MD simulations. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup. If you like our work, you will love our newsletter.

Deep Learning 128

Deep Learning Neural Network ML Artificial Intelligence 128

Marktechpost

JULY 30, 2024

In this approach, data scientists painstakingly transform raw data into formats suitable for ML models. Researchers from Stanford University, Kumo.AI, and the Max Planck Institute for Informatics introduced RelBench , a groundbreaking benchmark to facilitate deep learning on relational databases.

Deep Learning 120

Deep Learning Neural Network Categorization Data Extraction 120

AI News

MARCH 8, 2024

A job listing for an “Embodied Robotics Engineer” sheds light on the project’s goals, which include “designing, building, and maintaining open-source and low cost robotic systems that integrate AI technologies, specifically in deep learning and embodied AI.”

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Robotics Big Data Deep Learning Machine Learning 323

Unite.AI

JANUARY 27, 2025

David Driggers is the Chief Technology Officer at Cirrascale Cloud Services , a leading provider of deep learning infrastructure solutions. What sets Cirrascales AI Innovation Cloud apart from other GPUaaS providers in supporting AI and deep learning workflows?

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Deep Learning Data Quality ML Engineer Data Scientist 162

Marktechpost

JUNE 16, 2024

Topological Deep Learning (TDL) advances beyond traditional GNNs by modeling complex multi-way relationships, unlike GNNs that only capture pairwise interactions. Topological Neural Networks (TNNs), a subset of TDL, excel in handling higher-order relational data and have shown superior performance in various machine-learning tasks.

Deep Learning 130

Deep Learning Neural Network Machine Learning Explainability 130