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.

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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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ODSC - Open Data Science

JANUARY 25, 2023

A new deep learning algorithm just needs 12 seconds to determine if you’re above the legal drinking limit. The audio-based deep learning algorithm, ADLAIA, was trained to detect and identify alcohol inebriation levels based on a 12-second clip of their speech. How this algorithm works is interesting.

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Google Research AI blog

FEBRUARY 7, 2023

The explosion in deep learning a decade ago was catapulted in part by the convergence of new algorithms and architectures, a marked increase in data, and access to greater compute. Below, we highlight a panoply of works that demonstrate Google Research’s efforts in developing new algorithms to address the above challenges.

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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. There’s an excellent article about it as well.

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Heartbeat

MAY 2, 2023

Artificial intelligence has undergone a revolution thanks to deep learning. Deep learning allows machines to learn from vast amounts of data and carry out complex tasks that were previously only considered possible by humans (like translation between languages, recognizing objects etc.).

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Marktechpost

SEPTEMBER 1, 2023

Incorporating machine learning and deep learning algorithms has shown promise in bolstering security. In this context, a new article was published by a research team from the USA to address the growing security gap in mobile devices. Hybrid models, like CNN + SVM, show promise for improved performance.

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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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Analytics Vidhya

JUNE 15, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon What are Genetic Algorithms? Genetic Algorithms are search algorithms inspired by. The post Genetic Algorithms and its use-cases in Machine Learning appeared first on Analytics Vidhya.

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Analytics Vidhya

MARCH 20, 2024

Introduction Optimizing deep learning is a critical aspect of training efficient and accurate neural networks. Various optimization algorithms have been developed to improve the convergence speed.

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Marktechpost

OCTOBER 28, 2023

Harnessing the power of deep learning algorithms, researchers have delved into predictive medicine to discover potential treatments for osteoporosis. Using a sophisticated deep learning algorithm, the research team comprehensively analyzed differently expressed genes in mice. We are also on WhatsApp.

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Analytics Vidhya

JUNE 14, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In Neural Networks, we have the concept of Loss Functions, The post Complete Guide to Gradient-Based Optimizers in Deep Learning appeared first on Analytics Vidhya.

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Analytics Vidhya

JULY 25, 2022

This article was published as a part of the Data Science Blogathon. Introduction The gradient descent algorithm is an optimization algorithm mostly used in machine learning and deep learning. In linear regression, it finds weight and biases, and deep learning backward propagation uses the […].

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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. Loss functions guide learning by measuring errors. Activation functions introduce non-linear patterns.

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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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Analytics Vidhya

APRIL 23, 2022

This article was published as a part of the Data Science Blogathon. Introduction In this section, we will build a face detection algorithm using Caffe model, but only OpenCV is not involved this time. The post Face detection using the Caffe model appeared first on Analytics Vidhya.

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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.

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Analytics Vidhya

DECEMBER 12, 2022

This article was published as a part of the Data Science Blogathon. Introduction In machine learning and deep learning, the amount of data fed to the algorithm is one of the most critical factors affecting the model’s performance.

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Towards AI

AUGUST 21, 2023

Machine Learning vs. AI vs. Deep Learning vs. Neural Networks: What’s the Difference? The rapid evolution of technology is molding our everyday existence as businesses turn more and more to sophisticated algorithms for efficiency. Machine Learning (ML): Next, machine learning takes the spotlight.

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Analytics Vidhya

DECEMBER 11, 2022

This article was published as a part of the Data Science Blogathon. Introduction In machine learning, the data’s amount and quality are necessary to model training and performance. The amount of data affects machine learning and deep learning algorithms a lot.

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Viso.ai

DECEMBER 3, 2023

This article will explore the latest advances in pose analytics algorithms and AI vision techniques, their applications and use cases, and their limitations. Some popular 2D human pose estimation methods include OpenPose , CPN, AlphaPose, and HRNet (we will cover them and others later in this article).

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Heartbeat

NOVEMBER 14, 2023

For many years, gradient-boosting models and deep-learning solutions have won the lion's share of Kaggle competitions. XGBoost is not limited to machine learning tasks, as its incredible power can be harnessed when harmonized with deep learning algorithms. 2 (2021): 522–531.

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ODSC - Open Data Science

APRIL 24, 2023

Be sure to check out his talk, “ Fast Option Pricing Using Deep Learning Methods ,” there! Use the labeled training dataset to train deep neural networks Use the trained deep learning models as fast pricers Steps 1, 2, and 3 can be performed offline.

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Towards AI

APRIL 22, 2024

Algorithmic Bias in Facial Recognition Technologies Exploring how facial recognition systems can perpetuate biases. In this article, we will discuss the evolution of FR as a technology to where it is now, and then delve deeper into ethical concerns pertaining to biases which can perpetuate racial and sexual inequalities.

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Pickl AI

SEPTEMBER 15, 2024

Introduction Neural networks form the backbone of Deep Learning , allowing machines to learn from data by mimicking the human brain’s structure. Read Blog: Discovering Deep Boltzmann Machines (DBMs) in Deep Learning. Below are the key features that make them an essential tool in Deep Learning.

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Marktechpost

OCTOBER 4, 2023

In a groundbreaking development, a team of researchers from the Bioengineering Center and the Computational Health Center at Helmholtz Munich, in collaboration with the Technical University of Munich, has unveiled a deep-learning framework called DeepMB. Check out the Paper and Reference Article.

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Marktechpost

JULY 20, 2023

To assist with this problem, researchers develop a U3DTT technology, which stands for ‘underwater three-dimensional tactile tensegrity’ The U3DTT works on deep learning algorithms like Neural networks, Autoencoders, and Boltzmann machines. It also has diverse applications related to deep learning technologies.

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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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Analytics Vidhya

SEPTEMBER 10, 2021

This article was published as a part of the Data Science Blogathon What is Image Segmentation? The post Image Segmentation Algorithms With Implementation in Python – An Intuitive Guide appeared first on Analytics Vidhya. Image Segmentation helps to obtain the region of interest (ROI) from the image. It is done based […].

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Unite.AI

NOVEMBER 6, 2023

With these advancements, it’s natural to wonder: Are we approaching the end of traditional machine learning (ML)? In this article, we’ll look at the state of the traditional machine learning landscape concerning modern generative AI innovations. What is Traditional Machine Learning? What are its Limitations?

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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.

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Viso.ai

FEBRUARY 25, 2023

This article aims to provide an easy-to-understand overview of image segmentation and instance segmentation. In particular, you will learn about the following: What is Image Segmentation? Especially with the emergence of Deep Neural Networks (DNN) , image segmentation applications have made tremendous progress.

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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.

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Analytics Vidhya

NOVEMBER 1, 2021

This article was published as a part of the Data Science Blogathon Introduction In this article, we will cover everything from gathering data to preparing the steps for model training and evaluation. Deep learning algorithms can have huge functional uses when provided with quality data to sort through.

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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.

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Marktechpost

JULY 22, 2023

Recent achievements in supervised tasks of deep learning can be attributed to the availability of large amounts of labeled training data. Semi-supervised learning (SSL) aims to boost model performance using labeled and unlabeled input. Yet it takes a lot of effort and money to collect accurate labels.

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Viso.ai

DECEMBER 20, 2023

Huawei’s Mindspore is an open-source deep learning framework for training and inference written in C++. Our no-code solution enables teams to rapidly build real-world computer vision using the latest deep learning models out of the box. Adaptive Learning Rate. Operating under the Apache-2.0 Book a demo.

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