Marktechpost

JANUARY 19, 2024

Neural network-based methods in estimating biological age have shown high accuracy but lack interpretability, prompting the development of a biologically informed tool for interpretable predictions in prostate cancer and treatment resistance. The most noteworthy result was probably obtained for the pan-tissue dataset.

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Marktechpost

DECEMBER 18, 2023

In a groundbreaking study, MIT researchers have delved into the realm of deep neural networks, aiming to unravel the mysteries of the human auditory system. The foundation of this research builds upon prior work where neural networks were trained to perform specific auditory tasks, such as recognizing words from audio signals.

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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)? The two main types of traditional ML algorithms are supervised and unsupervised. Data Preprocessing and Feature Engineering: Traditional ML requires extensive preprocessing to transform datasets as per model requirements.

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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 are artificial neural networks built to handle data having a grid-like architecture, such as photos or movies.

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Marktechpost

SEPTEMBER 26, 2023

Microsoft researchers propose a groundbreaking solution to these challenges in their recent “Neural Graphical Models” paper presented at the 17th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2023). Check out the Paper and Reference Article.

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Towards AI

JULY 22, 2023

This is similar to how machine learning (ML) can seem at first. Our job is to explain complicated tech terms in a simple day-to-day language, so everyone can understand. Neural Networks: The Brainy Network Picture your brain. It’s a massive network of neurons connected by synapses. But don’t worry!

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Marktechpost

JULY 6, 2023

As a result of recent technological advances in machine learning (ML), ML models are now being used in a variety of fields to improve performance and eliminate the need for human labor. This is why when Explainable AI models can give a clear idea of why a decision was made but not how it arrived at that decision.

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Marktechpost

DECEMBER 5, 2023

The Hierarchically Gated Recurrent Neural Network (HGRN) technique developed by researchers from the Shanghai Artificial Intelligence Laboratory and MIT CSAI addresses the challenge of enhancing sequence modeling by incorporating forget gates in linear RNNs. Check out the Paper , Github, and Project.

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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. Additionally, Python has emerged as the primary language for various ML tasks. Students learn to implement and analyze models like linear models, kernel machines, neural networks, and graphical models.

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Marktechpost

JANUARY 28, 2024

Deep learning models, such as multilayer perceptrons, recurrent neural networks, and transformers, have been employed to forecast the fitness of genotypes based on experimental data. The study revealed that deep learning models are impressively effective, with some explaining over 90% of fitness variance in the data.

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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. Before being fed into the network, the photos are pre-processed and shrunk to the same size.

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AI News

DECEMBER 15, 2023

And that’s a big struggle,” explains Grande. Selecting efficient neural network architectures helps, as does compression techniques like quantisation to reduce precision without substantially impacting accuracy. The end-to-end development platform seamlessly integrates with all major cloud and ML platforms.

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Marktechpost

OCTOBER 8, 2023

By utilizing finely developed neural network architectures, we have models that are distinguished by extraordinary accuracy within their respective sectors. Despite their accurate performance, we must still fully understand how these neural networks function. We have new advancements that have been there with each day.

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Marktechpost

JULY 2, 2023

Thus, there is a growing demand for explainability methods to interpret decisions made by modern machine learning models, particularly neural networks. CRAFT addresses this limitation by harnessing modern machine learning techniques to unravel the complex and multi-dimensional visual representations learned by neural networks.

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Viso.ai

FEBRUARY 8, 2024

Restricted Boltzmann Machines A Restricted Boltzmann Machine is a two-layer probabilistic neural network. Benefits of DBNs Deep belief networks use probabilistic modeling and a supervised learning approach to offer certain benefits over conventional neural networks. Faster training and better results.

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Towards AI

FEBRUARY 20, 2024

Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction Everyone is using mobile or web applications which are based on one or other machine learning algorithms. Machine learning(ML) is evolving at a very fast pace. Machine learning(ML) is evolving at a very fast pace.

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Mlearning.ai

APRIL 24, 2023

One of the most popular and efficient approaches for object detection is the You Only Look Once version 5 (YOLOv5) neural network architecture. However, the YOLOv5 neural network architecture has several hyperparameters that can significantly affect its performance. BECOME a WRITER at MLearning.ai

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Mlearning.ai

MAY 11, 2023

Generative Pre-trained Transformer (GPT) Photo by Levart_Photographer on Unsplash Developed by OpenAI, GPT, which stands for “Generative Pre-trained Transformer,” is a neural network that has the ability to generate human-like language, making it an impressive tool for natural language processing (NLP).

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ML Review

MARCH 31, 2019

Source: Explaining and Harnessing Adversarial Examples , Goodfellow et al, ICLR 2015. We start with an image of a panda, which our neural network correctly recognizes as a “panda” with 57.7% Add a little bit of carefully constructed noise and the same neural network now thinks this is an image of a gibbon with 99.3%

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PyImageSearch

DECEMBER 11, 2023

Kicking Off with a Keynote The second day of the Google Machine Learning Community Summit began with an inspiring keynote session by Soonson Kwon, the ML Community Lead at Google. The focus of his presentation was clear and forward-thinking: Accelerate AI/ML research and application.

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Mlearning.ai

DECEMBER 31, 2023

Principles of Explainable AI( Source ) Imagine a world where artificial intelligence (AI) not only makes decisions but also explains them as clearly as a human expert. This isn’t a scene from a sci-fi movie; it’s the emerging reality of Explainable AI (XAI). What is Explainable AI? Complexity vs.

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Marktechpost

NOVEMBER 30, 2023

Researchers from Lund University and Halmstad University conducted a review on explainable AI in poverty estimation through satellite imagery and deep machine learning. The review underscores the significance of explainability for wider dissemination and acceptance within the development community.

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Heartbeat

SEPTEMBER 13, 2023

Source: ResearchGate Explainability refers to the ability to understand and evaluate the decisions and reasoning underlying the predictions from AI models (Castillo, 2021). Explainability techniques aim to reveal the inner workings of AI systems by offering insights into their predictions. What is Explainability?

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Marktechpost

MARCH 11, 2024

However, understanding their information-flow dynamics, learning mechanisms, and interoperability remains challenging, limiting their applicability in sensitive domains requiring explainability. These matrices are leveraged to develop class-agnostic and class-specific tools for explainable AI of Mamba models.

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Heartbeat

MARCH 6, 2023

Keras provides a simple API to build neural networks and uses Tensorflow as the backend. Before feeding these values to a neural network, the pixel values need to range from 0 to 1. Training the Neural Network In this section, you will build a neural network that requires configuring the layers of the model.

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Pickl AI

JANUARY 29, 2024

2024 Tech breakdown: Understanding Data Science vs ML vs AI Quoting Eric Schmidt , the former CEO of Google, ‘There were 5 exabytes of information created between the dawn of civilisation through 2003, but that much information is now created every two days.’ AI comprises Natural Language Processing, computer vision, and robotics.

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Heartbeat

FEBRUARY 15, 2023

Keras provides a simple API to build neural networks and uses Tensorflow as the backend. x_train <- vectorize_seq(train_data) x_test <- vectorize_seq(test_data) y_train <- as.numeric(train_labels) y_test <- as.numeric(test_labels) Training Neural Network Let’s use a simple architecture to build the network.

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Unite.AI

DECEMBER 1, 2023

Exploring the Techniques of LIME and SHAP Interpretability in machine learning (ML) and deep learning (DL) models helps us see into opaque inner workings of these advanced models. SHAP ( Source ) Both LIME and SHAP have emerged as essential tools in the realm of AI and ML, addressing the critical need for transparency and trustworthiness.

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ODSC - Open Data Science

JULY 26, 2023

As a senior data scientist, I often encounter aspiring data scientists eager to learn about machine learning (ML). The ML Process The machine learning process typically consists of the following steps: Data Collection Gathering relevant data is the first step in the machine learning process.

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Marktechpost

JANUARY 15, 2024

Normative models explain why people should make certain decisions based on principles, while explanatory models aim to capture how people decide. One recent study claims to have found a more accurate model for predicting human decisions using neural networks trained on a large online dataset called choices13k.

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AWS Machine Learning Blog

JULY 6, 2023

Many organizations choose SageMaker as their ML platform because it provides a common set of tools for developers and data scientists. Most of the options explained are also applicable if SageMaker is running in the SaaS AWS account. In some cases, an ISV may deploy their software in the customer AWS account.

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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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Towards AI

DECEMBER 19, 2023

Source: interpretable-ml-book The field of deep learning has grown exponentially and the recent craze about ChatGPT is proof of the same. For example, a deep neural net used for a loan application scorecard might deny a customer, and we will not be able to explain why. So, without further ado, let’s dive in! What is GAMINET?

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Mlearning.ai

JUNE 14, 2023

Learning LLMs (Foundational Models) Base Knowledge / Concepts: What is AI, ML and NLP Introduction to ML and AI — MFML Part 1 — YouTube What is NLP (Natural Language Processing)? — YouTube Transformer Neural Networks — EXPLAINED! YouTube BERT Research — Ep.

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Mlearning.ai

JULY 15, 2023

You have certainly seen it on Twitter, everyone is talking about this simple algorithm that beats powerful neural networks in… Continue reading on MLearning.ai »

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Marktechpost

DECEMBER 15, 2023

This method involves the application of a generative neural network, specifically a Generative Adversarial Network (GAN), a form of AI. According to researchers, this is the reason for developing GAN, an AI-based generative neural network trained using high-resolution radar precipitation fields.

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Marktechpost

APRIL 26, 2024

Notable examples include CrossBeam, which leverages execution states in sequence-to-sequence models, and specialized neural architectures like the instruction pointer attention graph neural networks. Also, don’t forget to follow us on Twitter. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup.

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