Marktechpost

MAY 20, 2024

Deep learning is a subset of machine learning that involves training neural networks with multiple layers to recognize patterns and make data-based decisions. This article lists the top courses in deep learning that provide comprehensive knowledge and practical skills necessary to excel in this transformative field.

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Marktechpost

AUGUST 3, 2024

Multi-layer perceptrons (MLPs) have become essential components in modern deep learning models, offering versatility in approximating nonlinear functions across various tasks. The difficulty in understanding learned representations limits their transparency, while expanding the network scale often proves complex.

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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. Task Automation AI software can easily handle repetitive, manual tasks (e.g.,

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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. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

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Marktechpost

MARCH 30, 2024

In 2024, the landscape of Python libraries for machine learning and deep learning continues to evolve, integrating more advanced features and offering more efficient and easier ways to build, train, and deploy models. PyTorch PyTorch is a widely used open-source machine learning library based on the Torch library.

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Marktechpost

MAY 28, 2024

Recent advancements in deep learning offer a transformative approach by enabling end-to-end learning models that can directly process raw biomedical data. Despite the promise of deep learning in healthcare, its adoption has been limited due to several challenges.

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Aiiot Talk

MAY 6, 2023

AI comprises numerous technologies like deep learning, machine learning, natural language processing, and computer vision. With the help of these technologies, AI is now capable of learning, reasoning, and processing complex data. This improvement has led to a significant advancement in medical diagnosis.

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Towards AI

NOVEMBER 19, 2023

This technique is more useful in the field of computer vision and natural language processing (NLP) because of large data that has semantic information. What is the issue of training deep learning models from scratch? It needs a lot of labeled data that takes more time and effort if not available publicly.It

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Marktechpost

APRIL 12, 2024

Deep learning architectures have revolutionized the field of artificial intelligence, offering innovative solutions for complex problems across various domains, including computer vision, natural language processing, speech recognition, and generative models.

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Marktechpost

OCTOBER 25, 2024

Natural Language Processing (NLP) is a rapidly growing field that deals with the interaction between computers and human language. As NLP continues to advance, there is a growing need for skilled professionals to develop innovative solutions for various applications, such as chatbots, sentiment analysis, and machine translation.

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Heartbeat

NOVEMBER 21, 2023

Computer vision, the field dedicated to enabling machines to perceive and understand visual data, has witnessed a monumental shift in recent years with the advent of deep learning. Photo by charlesdeluvio on Unsplash Welcome to a journey through the advancements and applications of deep learning in computer vision.

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IBM Journey to AI blog

FEBRUARY 14, 2024

Voice-based queries use natural language processing (NLP) and sentiment analysis for speech recognition so their conversations can begin immediately. Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed.

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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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Viso.ai

DECEMBER 20, 2023

In the field of computer vision, supervised learning and unsupervised learning are two of the most important concepts. In this guide, we will explore the differences and when to use supervised or unsupervised learning for computer vision tasks. What is supervised learning? About us: Viso.ai

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Unite.AI

SEPTEMBER 18, 2023

Artificial Intelligence is a very vast branch in itself with numerous subfields including deep learning, computer vision , natural language processing , and more. Another subfield that is quite popular amongst AI developers is deep learning, an AI technique that works by imitating the structure of neurons.

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Marktechpost

JUNE 3, 2024

Its AI courses offer hands-on training for real-world applications, enabling learners to effectively use Intel’s portfolio in deep learning, computer vision, and more. It covers AI fundamentals, including supervised learning and deep learning basics, without complex math.

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IBM Journey to AI blog

OCTOBER 12, 2023

Unlike basic machine learning models, deep learning models allow AI applications to learn how to perform new tasks that need human intelligence, engage in new behaviors and make decisions without human intervention. This allows intelligent machines to identify and classify objects within images and video footage.

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Analytics Vidhya

AUGUST 5, 2022

Introduction Image caption generator is the most fascinating application I found while working with NLP. This article was published as a part of the Data Science Blogathon. It’s cool to train your system to label the images you feed to it. As interesting as it sounds, it is equally challenging to implement this application. It […].

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Pickl AI

NOVEMBER 24, 2024

Summary: Autoencoders are powerful neural networks used for deep learning. Their applications include dimensionality reduction, feature learning, noise reduction, and generative modelling. By the end, you’ll understand why autoencoders are essential tools in Deep Learning and how they can be applied across different fields.

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AWS Machine Learning Blog

NOVEMBER 29, 2023

In today’s rapidly evolving landscape of artificial intelligence, deep learning models have found themselves at the forefront of innovation, with applications spanning computer vision (CV), natural language processing (NLP), and recommendation systems. use train_dataloader in the rest of the training logic.

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Unite.AI

MAY 29, 2024

Recent advancements in hardware such as Nvidia H100 GPU, have significantly enhanced computational capabilities. With nine times the speed of the Nvidia A100, these GPUs excel in handling deep learning workloads. These LLMs can perform various NLP operations, including data extraction.

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IBM Journey to AI blog

FEBRUARY 23, 2024

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. NLP translates the user’s words into machine actions, enabling machines to understand and respond to customer inquiries accurately. What makes a good AI conversationalist?

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Unite.AI

NOVEMBER 5, 2024

The need for specialized AI accelerators has increased as AI applications like machine learning, deep learning , and neural networks evolve. NVIDIA has been the dominant player in this domain for years, with its powerful Graphics Processing Units (GPUs) becoming the standard for AI computing worldwide.

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AI Weekly

APRIL 11, 2024

And this is particularly true for accounts payable (AP) programs, where AI, coupled with advancements in deep learning, computer vision and natural language processing (NLP), is helping drive increased efficiency, accuracy and cost savings for businesses. No legacy process is safe.

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AWS Machine Learning Blog

FEBRUARY 24, 2023

In recent years, advances in computer vision have enabled researchers, first responders, and governments to tackle the challenging problem of processing global satellite imagery to understand our planet and our impact on it. In this blog post we discussed using computer vision on satellite imagery.

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IBM Journey to AI blog

DECEMBER 15, 2023

PyTorch is an open-source AI framework offering an intuitive interface that enables easier debugging and a more flexible approach to building deep learning models. It is a popular choice among researchers and developers for rapid software development prototyping and AI and deep learning research.

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Marktechpost

JULY 31, 2024

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning This course teaches you how to use TensorFlow to build scalable AI models, starting with a soft introduction to Machine Learning and Deep Learning principles.

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Towards AI

JULY 23, 2023

In this article, we aim to focus on the development of one of the most powerful generative NLP tools, OpenAI’s GPT. Evolution of NLP domain after Transformers Before we start, let's take a look at the timeline of the works which brought great advancement in the NLP domain. Let’s see it step by step. In 2015, Andrew M.

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IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more.

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Flipboard

MARCH 27, 2023

In this series, you will learn about Accelerating Deep Learning Models with PyTorch 2.0. This lesson is the 1st of a 2-part series on Accelerating Deep Learning Models with PyTorch 2.0 : What’s New in PyTorch 2.0? Figure 7: Speedup in NLP models with PyTorch 2.0 Join me in computer vision mastery.

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Unite.AI

OCTOBER 27, 2024

The framework enables developers to build, train, and deploy machine learning models entirely in JavaScript, supporting everything from basic neural networks to complex deep learning architectures. What distinguishes TensorFlow.js is its comprehensive ecosystem and optimization capabilities.

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Unite.AI

OCTOBER 12, 2023

research scientist with over 16 years of professional experience in the fields of speech/audio processing and machine learning in the context of Automatic Speech Recognition (ASR), with a particular focus and hands-on experience in recent years on deep learning techniques for streaming end-to-end speech recognition.

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ODSC - Open Data Science

APRIL 11, 2023

A lot goes into NLP. Going beyond NLP platforms and skills alone, having expertise in novel processes, and staying afoot in the latest research are becoming pivotal for effective NLP implementation. We have seen these techniques advancing multiple fields in AI such as NLP, Computer Vision, and Robotics.

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Unite.AI

JULY 11, 2023

Introduction To Image Generation Image Source Course difficulty: Beginner-level Completion time: ~ 1 day (Complete the quiz/lab in your own time) Prerequisites: Knowledge of ML, Deep Learning (DL), Convolutional Neural Nets (CNNs), and Python programming. What will AI enthusiasts learn? What will AI enthusiasts learn?

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Marktechpost

FEBRUARY 27, 2024

Recent advancements in generative deep learning models have revolutionized fields such as Natural Language Processing (NLP) and Computer Vision (CV).

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Viso.ai

SEPTEMBER 2, 2024

As many areas of artificial intelligence (AI) have experienced exponential growth, computer vision is no exception. According to the data from the recruiting platforms – job listings that look for artificial intelligence or computer vision specialists doubled from 2021 to 2023.

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Towards AI

DECEMBER 28, 2023

The advent of more powerful personal computers paved the way for the gradual acceptance of deep learning-based methods. CS6910/CS7015: Deep Learning Mitesh M. Large Language Models – Deep dive into Transformers This is Part 1 of a course on LLMs as taught by AI4Bharat, IIT Madras' Prof.

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