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 318

Deep Learning Machine Learning Data Science Explainability 318

Marktechpost

MARCH 10, 2025

A researcher from New York University presents soft inductive biases as a key unifying principle in explaining these phenomena: rather than restricting hypothesis space, this approach embraces flexibility while maintaining a preference for simpler solutions consistent with data. However, deep learning remains distinctive in specific aspects.

Deep Learning 46

Deep Learning Convolutional Neural Networks Neural Network Explainability 46

Towards AI

JANUARY 31, 2025

Explaining a black box Deep learning model is an essential but difficult task for engineers in an AI project. Lets explore how to use the OmniXAI package in Python to examine and understand how an AI model makes decisions. Author(s): Chien Vu Originally published on Towards AI. This member-only story is on us.

Deep Learning 95

Deep Learning Computer Vision Explainability NLP 95

Flipboard

FEBRUARY 10, 2025

Using the Ollama API (this tutorial) To learn how to build a multimodal chatbot with Gradio, Llama 3.2, Gradio is an open-source Python library that enables developers to create user-friendly and interactive web applications effortlessly. curl ) and using the Python client ( ollama package). Want to Learn More About Ollama?

Chatbots 149

Chatbots Computer Vision Deep Learning Large Language Models 149

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 107

Neural Network Deep Learning Computer Vision Python 107

AWS Machine Learning Blog

DECEMBER 12, 2024

Amazon SageMaker has redesigned its Python SDK to provide a unified object-oriented interface that makes it straightforward to interact with SageMaker services. Shweta Singh is a Senior Product Manager in the Amazon SageMaker Machine Learning (ML) platform team at AWS, leading SageMaker Python SDK.

ML 84

ML Python Data Scientist Natural Language Processing 84

Marktechpost

APRIL 24, 2024

Explainable AI (XAI) aims to balance model explainability with high learning performance, fostering human understanding, trust, and effective management of AI partners. ELI5 is a Python package that helps debug machine learning classifiers and explain their predictions.

Explainable AI 114

Explainable AI Explainability Neural Network Data Scientist 114

Marktechpost

MAY 5, 2024

In recent years, the demand for AI and Machine Learning has surged, making ML expertise increasingly vital for job seekers. Additionally, Python has emerged as the primary language for various ML tasks. Machine Learning with Python This course covers the fundamentals of machine learning algorithms and when to use each of them.

Machine Learning 117

Machine Learning Python Neural Network Convolutional Neural Networks 117

PyImageSearch

JANUARY 13, 2025

Using Python # Load a model model = YOLO("yolo11n.pt") # Predict with the model results = model("[link] First, we load the YOLO11 object detection model. We must note 2 key points: The Python approach gives us more flexibility to integrate the model into larger projects and customize the outputs programmatically. Here, yolo11n.pt

Computer Vision 101

Computer Vision Python Deep Learning Neural Network 101

Unite.AI

OCTOBER 5, 2023

This is your third AI book, the first two being: “Practical Deep Learning: A Python-Base Introduction,” and “Math for Deep Learning: What You Need to Know to Understand Neural Networks” What was your initial intention when you set out to write this book? Different target audience.

Neural Network 292

Neural Network Deep Learning Machine Learning AI 292

Analytics Vidhya

JUNE 22, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction This article aims to explain Convolutional Neural Network and how. The post Building a Convolutional Neural Network Using TensorFlow – Keras appeared first on Analytics Vidhya.

Convolutional Neural Networks 400

Convolutional Neural Networks Neural Network Data Science Explainability 400

Analytics Vidhya

AUGUST 13, 2020

Introduction The SimCLR paper explains how this framework benefits from larger models and larger batch sizes and can produce results comparable to those of. The post How to Reduce Computational Constraints using Momentum Contrast V2(Moco-v2) in PyTorch appeared first on Analytics Vidhya.

Explainability 387

Explainability Deep Learning Python 387

Unite.AI

FEBRUARY 25, 2025

As AI systems increasingly power mission-critical applications across industries such as finance, defense, healthcare, and autonomous systems, the demand for trustworthy, explainable, and mathematically rigorous reasoning has never been higher. Raising the Bar in AI Reasoning Denis Ignatovich, Co-founder and Co-CEO of Imandra Inc.,

Automation 100

Automation Neural Network Explainability Algorithm 100

Flipboard

MARCH 24, 2025

Heres a quick recap of what you learned: Introduction to FastAPI: We explored what makes FastAPI a modern and efficient Python web framework, emphasizing its async capabilities, automatic API documentation, and seamless integration with Pydantic for data validation. transformers==4.30.2 datasets==2.13.1 Pillow==9.5.0 image as the base.

OpenAI 102

OpenAI Computer Vision Deep Learning Python 102

Analytics Vidhya

SEPTEMBER 27, 2022

” In that blog, I have explained: how to create a dataset directory, train, test and validation dataset splitting, and training from scratch. This article was published as a part of the Data Science Blogathon. Introduction My last blog discussed the “Training of a convolutional neural network from scratch using the custom dataset.”

Convolutional Neural Networks 364

Convolutional Neural Networks Neural Network Data Science Explainability 364

Marktechpost

MARCH 28, 2024

Deep Learning (Adaptive Computation and Machine Learning series) This book covers a wide range of deep learning topics along with their mathematical and conceptual background. It also provides information on the different deep learning techniques used in various industrial applications.

Artificial Intelligence 142

Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 142

Flipboard

MARCH 12, 2025

These are the best online AI courses you can take for free this month: A Gentle Introduction to Generative AI AI-900: Microsoft Azure AI Fundamentals AI Art Generation Guide: Create AI Images For Free AI Filmmaking AI for Beginners: Learn The Basics of ChatGPT AI for Business and Personal Productivity: A Practical Guide AI for Everyone AI Literacy (..)

Prompt Engineering 158

Prompt Engineering Prompt Engineer Artificial Intelligence Artificial Intelligence 158

Towards AI

FEBRUARY 6, 2025

to Artificial Super Intelligence and black box deep learning models. It details the underlying Transformer architecture, including self-attention mechanisms, positional embeddings, and feed-forward networks, explaining how these components contribute to Llamas capabilities. Enjoy the read!

Deep Learning 72

Deep Learning Computer Vision Large Language Models Explainability 72

PyImageSearch

SEPTEMBER 30, 2024

Home Table of Contents Introduction to GitHub Actions for Python Projects Introduction What Is CICD? For Python projects, CI/CD pipelines ensure that your code is consistently integrated and delivered with high quality and reliability. Git is the most commonly used VCS for Python projects, enabling collaboration and version tracking.

Python 100

Python Computer Vision Software Development Automation 100

Analytics Vidhya

JUNE 18, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon This article explains the problem of exploding and vanishing gradients while. The post The Challenge of Vanishing/Exploding Gradients in Deep Neural Networks appeared first on Analytics Vidhya.

Neural Network 329

Neural Network Data Science Explainability Algorithm 329

Analytics Vidhya

APRIL 19, 2024

It integrates vision, language, and action to explain and determine driving behavior. Introduction Wayve, a leading artificial intelligence company based in the United Kingdom, introduces Lingo-2, a groundbreaking system that harnesses the power of natural language processing.

Natural Language Processing 305

Natural Language Processing Artificial Intelligence Artificial Intelligence Explainability 305

Analytics Vidhya

MAY 5, 2019

It’s easy to explain how. Introduction “How did your neural network produce this result?” ” This question has sent many data scientists into a tizzy. The post A Guide to Understanding Convolutional Neural Networks (CNNs) using Visualization appeared first on Analytics Vidhya.

Convolutional Neural Networks 305

Convolutional Neural Networks Neural Network Data Scientist Explainability 305

Marktechpost

JUNE 28, 2024

Deep Learning (Adaptive Computation and Machine Learning series) This book covers a wide range of deep learning topics along with their mathematical and conceptual background. It also provides information on the different deep learning techniques used in various industrial applications.

Artificial Intelligence 114

Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 114

PyImageSearch

JANUARY 6, 2025

Python or R) to find the critical value from the -distribution for the chosen and degrees of freedom ( ). Performing the Grubbs Test In this section, we will see how to perform the Grubbs test in Python for sample datasets with small sample sizes. Note: We need to use statistical tables ( Table 1 ) or software (e.g., Thakur, eds.,

Python 117

Python Explainability Computer Vision Deep Learning 117

PyImageSearch

SEPTEMBER 23, 2024

Home Table of Contents Deploying a Vision Transformer Deep Learning Model with FastAPI in Python What Is FastAPI? You’ll learn how to structure your project for efficient model serving, implement robust testing strategies with PyTest, and manage dependencies to ensure a smooth deployment process. Testing main.py

Deep Learning 60

Deep Learning Python Computer Vision Software Development 60

Towards AI

JULY 21, 2023

People everywhere are working on some form of deep-learning-based computer vision projects. But before the advent of Deep Learning, image processing techniques were employed to manipulate and transform images in order to obtain insights that would help us achieve the task at hand. What does warping an image mean?

Computer Vision 98

Computer Vision Python Deep Learning Explainability 98

Marktechpost

NOVEMBER 16, 2024

Deep Learning (Adaptive Computation and Machine Learning series) This book covers a wide range of deep learning topics along with their mathematical and conceptual background. It also provides information on the different deep learning techniques used in various industrial applications.

Artificial Intelligence 105

Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 105

The MLOps Blog

MAY 10, 2023

How to save a trained model in Python? In this section, you will see different ways of saving machine learning (ML) as well as deep learning (DL) models. Note: The focus of this article is not to show you how you can create the best ML model but to explain how effectively you can save trained models.

Python 105

Python Metadata ML Machine Learning 105

ODSC - Open Data Science

MARCH 10, 2025

Tools like Python , R , and SQL were mainstays, with sessions centered around data wrangling, business intelligence, and the growing role of data scientists in decision-making. By 2017, deep learning began to make waves, driven by breakthroughs in neural networks and the release of frameworks like TensorFlow.

Data Science 52

Data Science Neural Network Convolutional Neural Networks Large Language Models 52

Marktechpost

MARCH 31, 2024

The book also provides Python code to explain these concepts. It is beginner-friendly, easy to comprehend, and includes not only theoretical concepts but also sample Python codes. It covers the basics of machine learning and Python and can even be read by those who have no prior knowledge of the language.

Data Science 117

Data Science Data Mining Machine Learning Neural Network 117

AWS Machine Learning Blog

JANUARY 25, 2023

Model explainability refers to the process of relating the prediction of a machine learning (ML) model to the input feature values of an instance in humanly understandable terms. This field is often referred to as explainable artificial intelligence (XAI). In this post, we illustrate the use of Clarify for explaining NLP models.

Explainability 84

Explainability Algorithm Natural Language Processing Machine Learning 84

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

Pickl AI

AUGUST 1, 2024

Summary : Deep Learning engineers specialise in designing, developing, and implementing neural networks to solve complex problems. Introduction Deep Learning engineers are specialised professionals who design, develop, and implement Deep Learning models and algorithms.

Deep Learning 52

Deep Learning Neural Network Machine Learning Natural Language Processing 52

Flipboard

MARCH 27, 2023

torch.compile Over the last few years, PyTorch has evolved as a popular and widely used framework for training deep neural networks (DNNs). The success of PyTorch is attributed to its simplicity, first-class Python integration, and imperative style of programming. torch.compile We start this lesson by learning to install PyTorch 2.0.

Neural Network 158

Neural Network Convolutional Neural Networks BERT Deep Learning 158

Flipboard

SEPTEMBER 4, 2023

Home Table of Contents Getting Started with Docker for Machine Learning Overview: Why the Need? These images also support interfacing with the GPU, meaning you can leverage it for training your Deep Learning networks written in TensorFlow. We guide you through setting up Docker on your system, explaining its significance in ML.

Machine Learning 153

Machine Learning Computer Vision Deep Learning Python 153

Marktechpost

SEPTEMBER 16, 2024

The course covers key RL methods like Monte Carlo and temporal difference learning, emphasizing algorithms and practical examples. Deep Learning and Reinforcement Learning (IBM) This course introduces deep learning and reinforcement learning, two key areas of machine learning.

Deep Learning 103

Deep Learning Neural Network Python Algorithm 103

IBM Journey to AI blog

JUNE 14, 2023

Traditional AI tools, especially deep learning-based ones, require huge amounts of effort to use. In addition, we recently open-sourced a preview of our python SDK and announced a partnership with Hugging Face to integrate their open-source libraries into watsonx.ai. That sounds like a joke, but we’re quite serious.

Automation 258

Automation Neural Network Natural Language Processing AI 258