This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
One of my favorite learning resources for gaining an understanding for the mathematics behind deeplearning is "Math for DeepLearning" by Ronald T. If you're interested in getting quickly up to speed with how deeplearning algorithms work at a basic level, then this is the book for you.
Introduction Efficient ML models and frameworks for building or even deploying are the need of the hour after the advent of Machine Learning (ML) and Artificial Intelligence (AI) in various sectors. PyTorch and Tensorflow have similar features, integrations, […] The post PyTorch vs TensorFlow: Which is Better for DeepLearning?
AI applications are everywhere. Generative AI hasn’t just transformed the way we work. As companies rush to implement generative AI solutions, there has been an […] The post 5 Free Courses to Master DeepLearning in 2024 appeared first on MachineLearningMastery.com.
If you want to stay ahead of the curve, networking with top AI minds, exploring cutting-edge innovations, and attending AI conferences is a must. According to Statista, the AI industry is expected to grow at an annual rate of 27.67% , reaching a market size of US$826.70bn by 2030. Lets dive in!
Today at NVIDIA GTC, Hewlett Packard Enterprise (NYSE: HPE) announced updates to one of the industry’s most comprehensive AI-native portfolios to advance the operationalization of generative AI (GenAI), deeplearning, and machine learning (ML) applications.
On Thursday, Google and the Computer History Museum (CHM) jointly released the source code for AlexNet , the convolutional neural network (CNN) that many credit with transforming the AI field in 2012 by proving that "deeplearning" could achieve things conventional AI techniques could not.
We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deeplearning. The team here at insideBIGDATA is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe.
Welcome insideBIGDATA AI News Briefs Bulletin Board, our timely new feature bringing you the latest industry insights and perspectives surrounding the field of AI including deeplearning, large language models, generative AI, and transformers.
We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deeplearning. The team here at insideAI News is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe.
We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deeplearning. The team here at insideBIGDATA is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe.
LLMs are advanced AI systems designed to understand and generate human-like text based on vast amounts of data. Introduction In today’s digital world, Large Language Models (LLMs) are revolutionizing how we interact with information and services.
In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deeplearning. Our industry is constantly accelerating with new products and services being announced everyday.
Generative AI is a branch of artificial intelligence that focuses on the creation of new content, such as text, images, music, and code. This is done by training machine learning models on large datasets of existing content, which the model then uses to generate new and original content. Want to build a custom large language model ?
Welcome insideBIGDATA AI News Briefs BULLETIN BOARD, our timely new feature bringing you the latest industry insights and perspectives surrounding the field of AI including deeplearning, large language models, generative AI, and transformers.
We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deeplearning. The team here at insideBIGDATA is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe.
We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deeplearning. The team here at insideBIGDATA is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe.
Welcome insideBIGDATA AI News Briefs BULLETIN BOARD, our timely new feature bringing you the latest industry insights and perspectives surrounding the field of AI including deeplearning, large language models, generative AI, and transformers.
Welcome insideBIGDATA AI News Briefs BULLETIN BOARD, our timely new feature bringing you the latest industry insights and perspectives surrounding the field of AI including deeplearning, large language models, generative AI, and transformers.
Apple researchers are advancing machine learning (ML) and AI through fundamental research that improves the worlds understanding of this technology and helps to redefine what is possible with it. This week, the Thirteenth International Conference on Learning Representations (ICLR) will be held in Singapore.
We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deeplearning. The team here at insideBIGDATA is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe.
In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deeplearning. Our industry is constantly accelerating with new products and services being announced everyday.
In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deeplearning. Our industry is constantly accelerating with new products and services being announced everyday.
This paper is a major turning point in deeplearning research. In this video presentation, Mohammad Namvarpour presents a comprehensive study on Ashish Vaswani and his coauthors' renowned paper, “Attention Is All You Need.”
Through tools like LIME and SHAP, we demonstrate how to gain insights […] The post ML and AI Model Explainability and Interpretability appeared first on Analytics Vidhya.
The collection includes free courses on Python, SQL, Data Analytics, Business Intelligence, Data Engineering, Machine Learning, DeepLearning, Generative AI, and MLOps.
In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deeplearning. Our industry is constantly accelerating with new products and services being announced everyday.
As part of #OpenSourceWeek Day 4, DeepSeek introduces 2 new tools to make deeplearning faster and more efficient: DualPipe and EPLB. These tools help improve how computers handle calculations and communication during training, making the process smoother and quicker.
Responsible AI is reaching new heights these days. Companies have started exploring Explainable AI as a means to explain the results better to senior leadership and increase their trust in AI Algorithms.
Our friends over at Scale are excited to introduce the 2nd edition of Scale Zeitgeist: AI Readiness Report! The company surveyed more than 1,600 executives and ML practitioners to uncover what’s working, what’s not, and the best practices for organizations to deploy AI for real business impact.
Author(s): Youssef Hosni Originally published on Towards AI. Docker containers offer significant advantages for machine learning by ensuring consistent, portable, and reproducible environments across different systems. In this article, we will explore 11 Docker container images for Generative AI and machine learning projects.
Gutierrez, insideAInews Editor-in-Chief & Resident Data Scientist, explores why mathematics is so integral to data science and machine learning, with a special focus on the areas most crucial for these disciplines, including the foundation needed to understand generative AI.
Relational Graph Transformers represent the next evolution in Relational DeepLearning, allowing AI systems to seamlessly navigate and learn from data spread across multiple tables.
Google Cloud worked with IDC on multiple studies involving global organizations across industries in order to explore how data leaders are successfully addressing key data and AI challenges. The company compiled the results in its 2023 Data and AI Trends report.
Last Updated on January 29, 2025 by Editorial Team Author(s): Vishwajeet Originally published on Towards AI. How to Become a Generative AI Engineer in 2025? From creating art and music to generating human-like text and designing virtual worlds, Generative AI is reshaping industries and opening up new possibilities.
In the recent discussion and advancements surrounding artificial intelligence, there’s a notable dialogue between discriminative and generative AI approaches. These methodologies represent distinct paradigms in AI, each with unique capabilities and applications. What is Generative AI?
In this contributed article, Maxime Vermeir, Senior Director of AI Strategy at ABBYY, discusses the term "AI Washing" which has emerged as a modern-day mirage, beguiling businesses into pouring resources into AI solutions that, unfortunately, fall short of solving real-world problems.
In this contributed article, April Miller, a senior IT and cybersecurity writer for ReHack Magazine, discusses how AI can help limit human error and improve data analysis accuracy. Explore how AI is fixing human error in data analytics and revolutionizing how we approach this critical field.
Generative AI technology offers a wide range of vertical use cases for software companies, high-tech firms, ISVs, and DNBs to meet efficiency demands and expedite workflows.
In the modern media landscape, artificial intelligence (AI) is becoming a crucial component for different mediums of production. This era of media production with AI will transform the world of entertainment and content creation. Thus, media personnel must adopt AI to stay relevant in today’s competitive media industry.
Our friends over at Pax8, a leading cloud commerce marketplace, released a new global report in collaboration with Microsoft and Channelnomics on the AI buying trends of Small and Midsize Businesses (SMBs).
As an example, the speech recognition community spent decades focusing on Hidden Markov Models at the expense of other architectures, before eventually being disrupted by advancements in deeplearning. Support Vector Machines were disrupted by deeplearning, and convolutional neural networks were displaced by transformers.
Welcome to the Generative AI Report round-up feature here on insideBIGDATA with a special focus on all the new applications and integrations tied to generative AI technologies. The combination of a LLM, fine tuned on proprietary data equals an AI application, and this is what these innovative companies are creating.
Gutierrez, insideAInews Editor-in-Chief & Resident Data Scientist, believes that as generative AI continues to evolve, its potential applications across industries are boundless. In this feature article, Daniel D.
We organize all of the trending information in your field so you don't have to. Join 17,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content