Analytics Vidhya

MAY 5, 2024

7B Explained appeared first on Analytics Vidhya. It is designed for a variety of code and natural language generation tasks. The 7B model is part of the Gemma family and is further trained on more than 500 billion tokens […] The post Is Coding Dead? Google’s CodeGemma 1.1

Explainability 257

Explainability Large Language Models AI Tools Generative AI 257

Marktechpost

MAY 14, 2024

Deep learning is crucial in today’s age as it powers advancements in artificial intelligence, enabling applications like image and speech recognition, language translation, and autonomous vehicles. Additionally, it offers insights into the diverse range of deep learning techniques applied across various industrial sectors.

Neural Network 99

Neural Network Deep Learning Computer Vision Python 99

Marktechpost

MAY 8, 2024

Over the past decade, advancements in deep learning and artificial intelligence have driven significant strides in self-driving vehicle technology. Deep learning and AI technologies play crucial roles in both modular and End2End systems for autonomous driving. Classical methodologies for these tasks are also explored.

Deep Learning 109

Deep Learning Neural Network Data Scarcity Natural Language Processing 109

Towards AI

JANUARY 27, 2023

Deep Learning Explained: Perceptron The key concept behind every neural network. Source: Image by Gerd Altmann from Pixabay Nowadays, frameworks such as Keras, TensorFlow, or PyTorch provide turnkey access to most deep learning solutions without necessarily having to understand them in depth.

Deep Learning 83

Deep Learning Explainability Neural Network Machine Learning 83

Analytics Vidhya

MAY 3, 2024

50 Billion AGI Gamble Explained! His vision represents a significant shift in the development of AI technologies, emphasizing the transformative potential of AGI across various societal sectors. Altman has […] The post Is Sam Altman Crazy or a Genius? $50 appeared first on Analytics Vidhya.

Explainability 266

Explainability OpenAI AI AI 266

Heartbeat

SEPTEMBER 13, 2023

Source: ResearchGate Explainability refers to the ability to understand and evaluate the decisions and reasoning underlying the predictions from AI models (Castillo, 2021). Explainability techniques aim to reveal the inner workings of AI systems by offering insights into their predictions. What is Explainability?

Explainability 52

Explainability Machine Learning Deep Learning Explainable AI 52

IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

Data Science 148

Data Science Machine Learning Big Data Data Mining 148

NYU Center for Data Science

NOVEMBER 9, 2023

Yann LeCun is a renowned deep learning pioneer and one of the most important minds in AI, and over the past few years he has been developing a comprehensive theory of machine learning, centered around “energy-based models,” which he calls “the only way to formalize and understand all model types.”

Deep Learning 98

Deep Learning Explainability Machine Learning AI 98

Marktechpost

NOVEMBER 30, 2023

Researchers from Lund University and Halmstad University conducted a review on explainable AI in poverty estimation through satellite imagery and deep machine learning. The review underscores the significance of explainability for wider dissemination and acceptance within the development community.

Deep Learning 97

Deep Learning AI Researcher AI Research Neural Network 97

Towards AI

FEBRUARY 3, 2024

(Left) Photo by Pawel Czerwinski on Unsplash U+007C (Right) Unsplash Image adjusted by the showcased algorithm Introduction It’s been a while since I created this package ‘easy-explain’ and published on Pypi. A few weeks ago, I needed an explainability algorithm for a YoloV8 model. The truth is, I couldn’t find anything.

Explainability 115

Explainability Explainable AI Neural Network AI 115

IBM Journey to AI blog

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029.

Machine Learning 129

Machine Learning ML Algorithm Chatbots 129

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. I’ve passed many ML courses before, so that I can compare.

Deep Learning 111

Deep Learning Neural Network ML Computer Vision 111

Heartbeat

FEBRUARY 21, 2024

Photo by Almos Bechtold on Unsplash Deep learning is a machine learning sub-branch that can automatically learn and understand complex tasks using artificial neural networks. Deep learning uses deep (multilayer) neural networks to process large amounts of data and learn highly abstract patterns.

Deep Learning 52

Deep Learning Neural Network Algorithm Machine Learning 52

NYU Center for Data Science

JANUARY 18, 2024

Micah Goldblum , a Postdoctoral Researcher at CDS, has created exactly that, in a recent survey intended to capture the multifaceted views of influential figures in deep learning. Goldblum’s work, the first in a planned series, aims to document diverse opinions in the field, particularly those not amplified by social media platforms.

Deep Learning 75

Deep Learning Machine Learning Explainability Data Science 75

Marktechpost

OCTOBER 8, 2023

The field of Machine Learning and Artificial Intelligence has become very important. The intricate and nonlinear nature of deep neural networks (DNNs) often leads to conclusions that may exhibit bias towards undesired or undesirable traits. We have new advancements that have been there with each day. Consequently, Prof.

Deep Learning 140

Deep Learning Neural Network Explainability Artificial Intelligence 140

Marktechpost

JANUARY 28, 2024

A researcher from the University of Zurich has turned to deep learning as a potent tool. Deep learning models, such as multilayer perceptrons, recurrent neural networks, and transformers, have been employed to forecast the fitness of genotypes based on experimental data. If you like our work, you will love our newsletter.

Explainability 114

Explainability Deep Learning Neural Network Machine Learning 114

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. We will explain intuitively what each one means and how it contributes to the deep learning process.

Deep Learning 116

Deep Learning Neural Network Natural Language Processing Machine Learning 116

Marktechpost

MARCH 31, 2024

Solving partial differential equations (PDEs) is complex, just like the events they explain. Deep learning, using designs like U-Nets, is popular for working with information at multiple levels of detail. Earlier methods of solving these equations struggled with the challenge of changes happening over time.

Deep Learning 135

Deep Learning Explainability ML Artificial Intelligence 135

Heartbeat

JUNE 12, 2023

Source: Author Introduction Machine learning model monitoring tracks the performance and behavior of a machine learning model over time. Organizations can ensure that their machine-learning models remain robust and trustworthy over time by implementing effective model monitoring practices.

Machine Learning 98

Machine Learning Data Drift Explainability Data Quality 98

Heartbeat

NOVEMBER 27, 2023

Deep learning automates and improves medical picture analysis. Convolutional neural networks (CNNs) can learn complicated patterns and features from enormous datasets, emulating the human visual system. Convolutional Neural Networks (CNNs) Deep learning in medical image analysis relies on CNNs.

Deep Learning 59

Deep Learning Convolutional Neural Networks Explainability Neural Network 59

Heartbeat

NOVEMBER 14, 2023

It has an excellent reputation as a tool for predicting many kinds of problems in data science and machine learning. For many years, gradient-boosting models and deep-learning solutions have won the lion's share of Kaggle competitions. In our next article, we can try an implementation of the model. 2 (2021): 522–531.

Deep Learning 52

Deep Learning Convolutional Neural Networks Neural Network Machine Learning 52

Heartbeat

NOVEMBER 29, 2023

Two names stand out prominently in the wide realm of deep learning: TensorFlow and PyTorch. These strong frameworks have changed the field, allowing researchers and practitioners to create and deploy cutting-edge machine learning models. TensorFlow and PyTorch present distinct routes to traverse.

Deep Learning 59

Deep Learning Neural Network Machine Learning Python 59

PyImageSearch

MAY 8, 2023

Home Table of Contents Introduction to Causality in Machine Learning Correlation and Causation Case Study 1: A “Marvelous” Problem Scenario 1: A Direct Cause Scenario 2: Reversing the Cause and Effect Scenario 3: Investigating a Hidden Cause Causal Thinking Case Study 2: Food App Conundrum Quiz Time! Let’s find out.

Machine Learning 111

Machine Learning Computer Vision Deep Learning Neural Network 111

ODSC - Open Data Science

OCTOBER 17, 2023

But without a strong understanding of deep learning, you’ll have a difficult time getting the most out of the cutting-edge developments in the industry. At ODSC West this October 30th to November 2nd, you’ll build the core knowledge and skills you need with the sessions in the deep learning track , such as the ones listed below.

Deep Learning 52

Deep Learning Machine Learning Data Scientist Data Science 52

ODSC - Open Data Science

FEBRUARY 13, 2023

With the rapid rise of machine learning in multiple industries, safety and security questions have arisen. Well according to our research, there is quite a lot going on in the world of machine learning safety and security. First are two techniques that tackle the question of why predictions are made and explain them.

Machine Learning 98

Machine Learning Explainability Data Science Explainable AI 98

Unite.AI

OCTOBER 5, 2023

I've so far read over 60 books on AI, and while some of them do get repetitive, this book managed to offer a fresh perspective, I enjoyed this book enough to add it to my personal list of the Best Machine Learning & AI Books of All Time. Below are some questions that were asked to author Ronald T. Different target audience.

Neural Network 298

Neural Network Deep Learning Machine Learning AI 298

DataRobot Blog

FEBRUARY 14, 2022

But just as important, you want it to be explainable. Explainability requirements continue after the model has been deployed and is making predictions. DataRobot offers end-to-end explainability to make sure models are transparent at all stages of their lifecycle. MLDev Explainability. Global Explainability .

Explainable AI 52

Explainable AI Explainability Machine Learning Data Drift 52

Heartbeat

OCTOBER 18, 2023

In this article, we embark on a journey to explore the transformative potential of deep learning in revolutionizing recommender systems. However, deep learning has opened new horizons, allowing recommendation engines to unravel intricate patterns, uncover latent preferences, and provide accurate suggestions at scale.

Deep Learning 52

Deep Learning Neural Network Machine Learning Algorithm 52

Analytics Vidhya

DECEMBER 3, 2021

Introduction In this article, I will attempt to explain all of the ideas that you should be familiar with about databases. As we all know, while working on a Data Science, Machine Learning, Deep Learning, or another project, the most important element is […].

Data Science 288

Data Science Deep Learning Explainability Machine Learning 288

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. As soon as the system adapts to human wants, it automates the learning process accordingly.

Computer Vision 107

Computer Vision Deep Learning Neural Network Artificial Intelligence 107

Analytics Vidhya

AUGUST 26, 2021

This article was published as a part of the Data Science Blogathon “You can have data without information but you cannot have information without data” – Daniel Keys Moran Introduction If you are here then you might be already interested in Machine Learning or Deep Learning so I need not explain what it is?

Deep Learning 268

Deep Learning Explainability Machine Learning Data Science 268

Towards AI

JULY 17, 2023

In machine learning, we usually model problems as functions. About this series In this series, we will learn how to code the must-to-know deep learning algorithms such as convolutions, backpropagation, activation functions, optimizers, deep neural networks, and so on using only plain and modern C++.

Deep Learning 68

Deep Learning Machine Learning Neural Network Artificial Intelligence 68

Heartbeat

AUGUST 1, 2023

A World of Computer Vision Outside of Deep Learning Photo by Museums Victoria on Unsplash IBM defines computer vision as “a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs [1].”

Computer Vision 52

Computer Vision Deep Learning Neural Network Algorithm 52

Heartbeat

SEPTEMBER 6, 2023

Experimenting with Comet, a machine learning platform Photo by Donny Jiang on Unsplash Creating a machine learning model is easy, but that’s not what machine learning is all about. There are machine learning platforms that can perform all these tasks, and Comet is one such platform.

Machine Learning 52

Machine Learning Deep Learning Auto-complete Data Scientist 52

Heartbeat

SEPTEMBER 7, 2023

In the ever-evolving landscape of machine learning and artificial intelligence, understanding and explaining the decisions made by models have become paramount. Enter Comet , that streamlines the model development process and strongly emphasizes model interpretability and explainability. Why Does It Matter?

Explainability 52

Explainability Machine Learning Data Scientist Deep Learning 52

Google Research AI blog

MARCH 14, 2023

Developing machine learning (ML) tools in pathology to assist with the microscopic review represents a compelling research area with many potential applications. To our knowledge, this is the first demonstration of pathologists learning to identify and score a specific pathology feature originally identified by an ML-based approach.

Deep Learning 95

Deep Learning ML Machine Learning Explainability 95

Unite.AI

DECEMBER 1, 2023

Machine learning , a subset of AI, involves three components: algorithms, training data, and the resulting model. An algorithm, essentially a set of procedures, learns to identify patterns from a large set of examples (training data). The culmination of this training is a machine-learning model.

LLM 264

LLM Machine Learning Explainability Algorithm 264