Flipboard

JULY 31, 2023

In this post, we’ll show you the datasets you can use to build your machine learning projects. After you create a free account, you’ll have access to the best machine learning datasets. Importance and Role of Datasets in Machine Learning Data is king.

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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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AWS Machine Learning Blog

MARCH 21, 2025

JupyterLab applications flexible and extensive interface can be used to configure and arrange machine learning (ML) workflows. We use JupyterLab to run the code for processing formulae and charts. Amazon Simple Storage Service (Amazon S3) Amazon S3 is an object storage service built to store and protect any amount of data.

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Viso.ai

JANUARY 2, 2024

In the following, we will explore Convolutional Neural Networks (CNNs), a key element in computer vision and image processing. Whether you’re a beginner or an experienced practitioner, this guide will provide insights into the mechanics of artificial neural networks and their applications. Howard et al.

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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.

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Heartbeat

DECEMBER 20, 2023

Whether you’re a seasoned AI researcher or a budding enthusiast in machine learning, the insights offered here will deepen your understanding and guide you in leveraging the full potential of CNNs in various applications. The net result of both of these scenarios is that early layers in the network become more challenging to train.

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Heartbeat

MARCH 1, 2023

Before being fed into the network, the photos are pre-processed and shrunk to the same size. A convolutional neural network (CNN) is primarily used for image classification. Convolutional, pooling, and fully linked layers are some of the layers that make up a CNN. X_train = X_train / 255.0 X_test = X_test / 255.0

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ODSC - Open Data Science

MARCH 10, 2025

Over the past decade, data science has undergone a remarkable evolution, driven by rapid advancements in machine learning, artificial intelligence, and big data technologies. By 2017, deep learning began to make waves, driven by breakthroughs in neural networks and the release of frameworks like TensorFlow.

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NYU Center for Data Science

SEPTEMBER 25, 2024

CDS announced a new course in the center’s newly launched Lifelong Learning Program. Foundations of Deep Learning” offers CDS alumni the chance to dive into the latest advancements in AI and machine learning. I interact with animations, and when I explain mathematical concepts, the math pops up in the background.

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AWS Machine Learning Blog

DECEMBER 7, 2023

Amazon Forecast is a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts. Calculating courier requirements The first step is to estimate hourly demand for each warehouse, as explained in the Algorithm selection section.

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TransOrg Analytics

FEBRUARY 11, 2025

As AI continues integrating into every aspect of society, the need for Explainable AI (XAI) becomes increasingly important. Understanding the AI Black Box Problem AI enables machines to mimic human intelligence by learning, reasoning, and making decisions. What is Explainable AI? Why is Explainable AI Important?

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Pickl AI

AUGUST 14, 2024

Summary: Neural networks are a key technique in Machine Learning, inspired by the human brain. They consist of interconnected nodes that learn complex patterns in data. Reinforcement Learning: An agent learns to make decisions by receiving rewards or penalties based on its actions within an environment.

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Artificial Corner

JANUARY 23, 2025

The course will show you how to set up Python, teach you how to print your first “Hello World”, and explain all the core concepts in Python. Of course, to do all of this you will need to have at least a basic understanding of data analysis libraries such as Pandas and Scikit-learn. #4 That’s it!

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Pickl AI

AUGUST 28, 2024

It also includes practical implementation steps and discusses the future of classification in Machine Learning. Introduction Machine Learning has revolutionised the way we analyse and interpret data, enabling machines to learn from historical data and make predictions or decisions without explicit programming.

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PyImageSearch

NOVEMBER 13, 2023

For example, image classification, image search engines (also known as content-based image retrieval, or CBIR), simultaneous localization and mapping (SLAM), and image segmentation, to name a few, have all been changed since the latest resurgence in neural networks and deep learning. 2015 ), SSD ( Fei-Fei et al., MobileNets ).

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Heartbeat

FEBRUARY 6, 2023

In the second step, these potential fields are classified and corrected by the neural network model. R-CNN (Regions with Convolutional Neural Networks) and similar two-stage object detection algorithms are the most widely used in this regard. However, this algorithm is slower than other algorithms.

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Towards AI

MAY 15, 2024

Source: Author/Adobe Firefly) Last week, as I scrolled through my Instagram feed, an animation video popped up in the famous 3Blue1Brown style explaining how Convolution Neural Networks work. First, generate a 2-minute transcript explaining the transformers architecture at a high-level. to explain what concepts.

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Heartbeat

FEBRUARY 22, 2023

Deep learning for feature extraction, ensemble models, and more Photo by DeepMind on Unsplash The advent of deep learning has been a game-changer in machine learning, paving the way for the creation of complex models capable of feats previously thought impossible.

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Unite.AI

OCTOBER 10, 2024

A new research paper from Canada has proposed a framework that deliberately introduces JPEG compression into the training scheme of a neural network, and manages to obtain better results – and better resistance to adversarial attacks. In contrast, JPEG-DL (right) succeeds in distinguishing and delineating the subject of the photo.

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Mlearning.ai

FEBRUARY 25, 2023

In the same way, artificial neural networks (ANNs) were developed inspired by neurons in the brain. Complex machine-learning problems such as image classification, recommendation systems, and language-to-language translation have been solved with this technique. ANNs are the core of deep learning. What is ANN?

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Marktechpost

DECEMBER 15, 2023

In this manner, from coarsely resolved data, the GAN learns how to produce realistic precipitation fields and determine their temporal sequence. Compared to trilinear interpolation and a classical convolutional neural network, the generative model reconstructs the resolution-dependent extreme value distribution with high skill.

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Pickl AI

JULY 22, 2024

Summary: Probabilistic model in Machine Learning handle uncertainty and complex data structures, improving decision-making and predictions. Introduction Machine Learning models are essential tools in Data Science , designed to predict outcomes and uncover patterns from data.

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Pickl AI

NOVEMBER 28, 2024

Summary: The blog discusses essential skills for Machine Learning Engineer, emphasising the importance of programming, mathematics, and algorithm knowledge. Understanding Machine Learning algorithms and effective data handling are also critical for success in the field. billion in 2022 and is expected to grow to USD 505.42

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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.

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Heartbeat

SEPTEMBER 25, 2023

Photo by National Cancer Institute on Unsplash Machine learning has recently been a game-changer in healthcare and medical diagnosis. This is where machine learning comes in. Furthermore, machine learning algorithms are revolutionizing the concept of personalized medicine.

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Viso.ai

NOVEMBER 27, 2024

YOLO (You Only Look Once) is a family of real-time object detection machine-learning algorithms. Object detection is a computer vision task that uses neural networks to localize and classify objects in images. To learn more, book a demo with our team. Viso Suite is the end-to-End, No-Code Computer Vision Solution.

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Mlearning.ai

JUNE 8, 2023

Vector Embeddings for Developers: The Basics | Pinecone Used geometry concept to explain what is vector, and how raw data is transformed to embedding using embedding model. Pinecone Used a picture of phrase vector to explain vector embedding. What are Vector Embeddings? using its Spectrogram ).

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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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Viso.ai

MAY 7, 2024

GoogLeNet’s deep learning model was deeper than all the previous models released, with 22 layers in total. Increasing the depth of the Machine Learning model is intuitive, as deeper models tend to have more learning capacity and as a result, this increases the performance of a model.

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Marktechpost

JUNE 27, 2023

Raw Shorts To assist organizations in making explainer films, animations, and promotional movies for the web and social media, Raw Shorts provides a text-to-video creator and a video editor driven by artificial intelligence. It employs machine learning techniques to read a screenplay and extract the plot points to locate appropriate media.

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ML Review

DECEMBER 16, 2019

Machine Learning on Graphs becomes a first-class citizen at AI conferences while being not that mysterious as you might have imagined ?. NeurIPS’18 presented several papers with deep theoretical studies of building hyperbolic neural nets. Hu, Liu et al propose and explain one of the first frameworks for pre-training GNNs.

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Mlearning.ai

MAY 11, 2023

In addition to GPT, there are many other types of neural networks that are used in AI and machine learning applications. Here are a few examples: Convolutional Neural Networks (CNNs): These are often used in image recognition tasks, as they can identify patterns and features in images.

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Neural Network Explainability Convolutional Neural Networks Natural Language Processing 52

Heartbeat

JUNE 27, 2023

Neural networks leverage the structure and properties of graph and work in a similar fashion. Graph Neural Networks are a class of artificial neural networks that can be represented as graphs. Similarly, RNNs can be applied to graph structures where each node is represented by a word.

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Viso.ai

FEBRUARY 8, 2024

On the other hand, the advances in conventional deep networks, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Artificial Neural Networks (ANNs), have provided ground-breaking results. Book a demo to learn more about the Viso suite.

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Viso.ai

DECEMBER 18, 2023

ONNX is an open standard for representing computer vision and machine learning models. The ONNX standard provides a common format enabling the transfer of models between different machine learning frameworks such as TensorFlow, PyTorch , MXNet, and others. A widely-used open-source machine learning library from Facebook.

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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. DFF identifies regions in the network’s feature space that belong to the same semantic concept.

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Heartbeat

MAY 2, 2023

To train a neural network you give the network a set of data and it compares the output with the desired output, the difference between the two will be known as an error which will be used in adjusting the weights till the outputs align. We’re committed to supporting and inspiring developers and engineers from all walks of life.

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