Unite.AI

MAY 31, 2023

A neural network (NN) is a machine learning algorithm that imitates the human brain's structure and operational capabilities to recognize patterns from training data. Despite being a powerful AI tool, neural networks have certain limitations, such as: They require a substantial amount of labeled training data.

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Mlearning.ai

FEBRUARY 22, 2023

Machine learning interview preparation: computer vision, convolutional neural network, pooling, popular convolutional neural networks Continue reading on MLearning.ai »

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Heartbeat

AUGUST 21, 2023

In this guide, we’ll talk about Convolutional Neural Networks, how to train a CNN, what applications CNNs can be used for, and best practices for using CNNs. What Are Convolutional Neural Networks CNN? CNNs learn geometric properties on different scales by applying convolutional filters to input data.

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Analytics Vidhya

APRIL 19, 2024

Introduction Embark on a thrilling journey into the domain of Convolutional Neural Networks (CNNs) and Skorch, a revolutionary fusion of PyTorch’s deep learning prowess and the simplicity of scikit-learn.

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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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Flipboard

FEBRUARY 2, 2023

Learn the basics of machine learning, including classification, SVM, decision tree learning, neural networks, convolutional, neural networks, boosting, and K nearest neighbors.

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Analytics Vidhya

APRIL 15, 2024

Introduction Welcome to an in-depth exploration of ship classification using Convolutional Neural Networks (CNNs) with the Analytics Vidhya hackathon dataset. CNNs are a cornerstone of image-related tasks, known for their ability to learn hierarchical representations of images.

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Marktechpost

MAY 5, 2024

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

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Heartbeat

MARCH 1, 2023

Tracking your image classification experiments with Comet ML Photo from nmedia on Shutterstock.com Introduction Image classification is a task that involves training a neural network to recognize and classify items in images. A dataset of labeled images is used to train the network, with each image given a particular class or label.

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Analytics Vidhya

DECEMBER 31, 2023

A lightweight convolutional neural network (CNN) architecture, MobileNetV2, is specifically […] The post What is MobileNetV2? This article explores MobileNetV2’s architecture, training methodology, performance assessment, and practical implementation. What is MobileNetV2?

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Marktechpost

SEPTEMBER 10, 2023

The post Unlocking the Secrets of Catalytic Performance with Deep Learning: A Deep Dive into the ‘Global + Local’ Convolutional Neural Network for High-Precision Screening of Heterogeneous Catalysts appeared first on MarkTechPost. If you like our work, you will love our newsletter.

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Analytics Vidhya

MAY 27, 2023

Introduction The UNet is the first model that comes to mind these days whenever we want to use image segmentation in machine learning. Extensive medical imaging, autonomous driving, and satellite imaging applications are all supported by the encoder-decoder convolutional neural network UNet.

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Analytics Vidhya

OCTOBER 9, 2022

Introduction In recent times, whenever we wish to perform image segmentation in machine learning, the first model we think of is the U-Net. U-Net is an encoder-decoder convolutional neural network with […]. It has been revolutionary in performance improvement compared to previous state-of-the-art methods.

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Marktechpost

APRIL 11, 2024

MIT researchers have proposed a method that combines first-principles calculations and machine learning to address the challenge of computationally expensive and intractable calculations required to understand the thermal conductivity of semiconductors, specifically focusing on diamonds.

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SAS Software

APRIL 27, 2023

In her first blog post, SAS' Mu He shows you how to train a convolutional neural network that can accurately detect patients with COVID-19 using the transfer learning technique. The post Using SAS Viya Machine Learning to classify COVID from non-COVID appeared first on SAS Blogs.

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Chatbots Life

MAY 16, 2024

IF THERE IS A SIN, THIS IS THE ONLY SIN; TO SAY THAT YOU ARE WEAK, OR OTHERS ARE WEAK” - By Swami Vivekanand Is Deep Learning now overtaking the Machine Learning algorithm? Let us first know what is Machine Learning ? Machine Learning was coined by “ Arthur Samuel ” in the year 1959.

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Towards AI

MARCH 17, 2023

Last time I showed you how to train a simple PyTorch model, this was an introduction to PyTorch where I showed you how to train an MNIST classifier with Convolutional Neural Networks. [link] Welcome everyone back to my other tutorial. We achieved a high accuracy rate of 97–98%, which means it’s very accurate.

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NYU Center for Data Science

JANUARY 31, 2024

The idea that neural networks undergo distinct developmental phases during training has long been a subject of debate and fascination. Published in the Transactions on Machine Learning Research (TMLR) , Hu’s work offers new insights into the training dynamics of neural networks.

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Analytics Vidhya

MARCH 10, 2020

Starting your Deep Learning Career? Deep learning can be a complex and daunting field for newcomers. Concepts like hidden layers, convolutional neural networks, backpropagation. The post Getting into Deep Learning? Here are 5 Things you Should Absolutely Know appeared first on Analytics Vidhya.

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Analytics Vidhya

FEBRUARY 16, 2022

Since 2012 after convolutional neural networks(CNN) were introduced, we moved away from handcrafted features to an end-to-end approach using deep neural networks. The post Classification without Training Data: Zero-shot Learning Approach appeared first on Analytics Vidhya.

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Towards AI

APRIL 7, 2024

With the emergence of ARCGISpro which will replace ArcMap by 2026 mainly focusing on data science and machine learning, all the signs that machine learning is the future of GIS and you might have to learn some principles of data science, but where do you start, let us have a look.

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Mlearning.ai

MAY 30, 2023

Recurrent Neural Networks (RNNs) have become a potent tool for analysing sequential data in the large subject of artificial intelligence and machine learning. As we know that Convolutional Neural Network (CNN) is used for structured arrays of data such as image data. RNN is used for sequential data.

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AI Weekly

OCTOBER 26, 2023

cryptopolitan.com Applied use cases Alluxio rolls out new filesystem built for deep learning Alluxio Enterprise AI is aimed at data-intensive deep learning applications such as generative AI, computer vision, natural language processing, large language models and high-performance data analytics. voxeurop.eu

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Mlearning.ai

MAY 21, 2023

CNNs with random weights are very useful even without training! Continue reading on MLearning.ai »

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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.

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AI News

JULY 27, 2023

The collaboration combines the strengths of three industry leaders: Graphcore, renowned for its Intelligence Processing Units (IPUs) hardware; UbiOps, a powerful machine learning operations (MLOps) platform; and Gcore Cloud, known for its robust cloud infrastructure.

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Towards AI

MAY 9, 2024

The hypothesis is centered on whether we can predict the success or failure of an IPO using machine learning. You will also understand the basics of convolutional neural networks, different image processing strategies for feature generation, and dimensionality reduction techniques for improving computational complexity.

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Mlearning.ai

FEBRUARY 14, 2023

Image classification is a field of study within the broader area of computer vision and deep learning, with the goal of automating the… Continue reading on MLearning.ai »

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Pickl AI

AUGUST 3, 2023

Introduction to Deep Learning Algorithms: Deep learning algorithms are a subset of machine learning techniques that are designed to automatically learn and represent data in multiple layers of abstraction. The initial weights and biases of the neural network are randomly assigned.

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Viso.ai

DECEMBER 19, 2023

Today, the use of convolutional neural networks (CNN) is the state-of-the-art method for image classification. Image Classification Using Machine Learning CNN Image Classification (Deep Learning) Example applications of Image Classification Let’s dive deep into it! How Does Image Classification Work?

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Mlearning.ai

JULY 17, 2023

How taking inspiration from the brain can help us create Neural Networks. One of the most promising avenues for this kind of research is to learn from evolution and biological systems to improve the design of AI Models (after all Neural Networks were based on our brains). About the Author: William A. Lambos , M.S.,

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Marktechpost

APRIL 12, 2024

This article explores some of the most influential deep learning architectures: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Transformers, and Encoder-Decoder architectures, highlighting their unique features, applications, and how they compare against each other.

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Towards AI

APRIL 27, 2023

Understanding the Principles, Challenges, and Applications of Gradient Descent Image by Author with @MidJourney Introduction to Gradient Descent Gradient descent is a fundamental optimization algorithm used in machine learning and data science to find the optimal values of the parameters in a model.

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Marktechpost

JULY 21, 2023

The Multi-Task Convolutional Neural Network (MTCNN) and VGG19 neural network were used for facial detection and emotional recognition, respectively. In Study 1, researchers used the facial emotion detection method to analyze the emotional features from the recorded video frames.

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Marktechpost

SEPTEMBER 1, 2023

Incorporating machine learning and deep learning algorithms has shown promise in bolstering security. In addition, the study highlights that hybrid schemes combining deep learning features with deep learning/machine learning classification can significantly improve authentication performance.

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Viso.ai

MAY 10, 2024

Whether you’re building a consumer app to recognize plant species or an enterprise tool to monitor office security camera footage, you are going to need to build a Machine Learning (ML) model to provide the core functionality. Building a machine learning model consists of 7 high-level steps: 1.

Machine Learning 52

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Heartbeat

NOVEMBER 14, 2023

Integrating XGboost with Convolutional Neural Networks Photo by Alexander Grey on Unsplash XGBoost is a powerful library that performs gradient boosting. It has an excellent reputation as a tool for predicting many kinds of problems in data science and machine learning. It was envisioned by Thongsuwan et al.,

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