Analytics Vidhya

FEBRUARY 10, 2020

Overview Convolutional neural networks (CNNs) are all the rage in the deep learning and computer vision community How does this CNN architecture work? The post Demystifying the Mathematics Behind Convolutional Neural Networks (CNNs) appeared first on Analytics Vidhya. We’ll.

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Analytics Vidhya

MARCH 10, 2022

Apple’s Siri and Google’s voice search both use Recurrent Neural Networks (RNNs), which are the state-of-the-art method for sequential data. It’s the first algorithm with an internal memory that remembers its input, making it perfect for problems involving sequential data in machine learning.

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Analytics Vidhya

JUNE 18, 2021

The post The Challenge of Vanishing/Exploding Gradients in Deep Neural Networks appeared first on Analytics Vidhya. ArticleVideo Book This article was published as a part of the Data Science Blogathon This article explains the problem of exploding and vanishing gradients while.

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Analytics Vidhya

SEPTEMBER 12, 2023

Introduction Neuroevolution is a captivating field where AI merges neural networks and evolutionary algorithms to nurture its creative abilities. It’s akin to AI’s artistic or musical journey, allowing it to paint masterpieces and compose symphonies.

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Analytics Vidhya

AUGUST 23, 2021

Image by my great learning Introduction Gradient descent is an optimization algorithm that is used to train machine learning models and is now used in a neural network. This article was published as a part of the Data Science Blogathon Building a simple Machine Learning model using Pytorch from scratch.

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Marktechpost

MAY 14, 2024

This article lists the top Deep Learning and Neural Networks books to help individuals gain proficiency in this vital field and contribute to its ongoing advancements and applications. Deep Learning with Python “Deep Learning with Python” introduces deep learning with the help of Python and its Keras library.

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Analytics Vidhya

FEBRUARY 22, 2023

Introduction From the 2000s onward, Many convolutional neural networks have been emerging, trying to push the limits of their antecedents by applying state-of-the-art techniques. The ultimate goal of these deep learning algorithms is to mimic the human eye’s capacity to perceive the surrounding environment.

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TensorFlow

FEBRUARY 6, 2024

Yet most machine learning (ML) algorithms allow only for regular and uniform relations between input objects, such as a grid of pixels, a sequence of words, or no relation at all. Apart from making predictions about graphs, GNNs are a powerful tool used to bridge the chasm to more typical neural network use cases.

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Analytics Vidhya

JULY 25, 2022

It uses Machine Learning-based Model Algorithms and Deep Learning-based Neural Networks for its implementation. […]. Introduction Computer Vision Is one of the leading fields of Artificial Intelligence that enables computers and systems to extract useful information from digital photos, movies, and other visual inputs.

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Analytics Vidhya

OCTOBER 20, 2021

we are now at a point where deep learning and neural networks are so powerful that can […]. The post An End-to-End Introduction to Generative Adversarial Networks(GANs) appeared first on Analytics Vidhya. The technological advancement in different sectors has left everyone shocked.

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Marktechpost

MAY 5, 2024

Additionally, Python has emerged as the primary language for various ML tasks. This article outlines the top ML courses in Python, offering readers the opportunity to enhance their skill set, transition careers, and meet the expectations of recruiters. and evaluating the same.

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AssemblyAI

SEPTEMBER 4, 2023

Traditional compression algorithms have been centered on reducing redundancies in data sequences –be it in images, videos, or audio– with a high reduction in file size at the cost of some loss of information from the original. At its core, it's an end-to-end neural network-based approach.

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Marktechpost

MARCH 26, 2024

In order to address these challenges, a team of researchers has introduced DomainLab, a modular Python package for domain generalization in deep learning. This python package seeks to disentangle the elements of domain generalization techniques so that users can more readily mix various algorithmic components.

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Analytics Vidhya

OCTOBER 25, 2023

While the brain’s inner workings remain a mystery, we can liken it to a versatile neural network. Introduction Have you ever wondered how our intricate brains process the world? Thanks to electrochemical signals, it handles various data types – audio, visuals, smells, tastes, and touch.

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Unite.AI

OCTOBER 27, 2024

The ecosystem has rapidly evolved to support everything from large language models (LLMs) to neural networks, making it easier than ever for developers to integrate AI capabilities into their applications. is its intuitive approach to neural network training and implementation. environments. TensorFlow.js TensorFlow.js

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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. Below are the top ten Python libraries that stand out in AI development.

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Unite.AI

DECEMBER 18, 2023

Position-wise Feed-Forward Networks : After attention, a simple neural network processes the output of each position separately and identically. Hardware-aware Algorithm : Mamba uses a parallel algorithm that's optimized for modern hardware, especially GPUs.

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Marktechpost

MARCH 28, 2024

Python: Advanced Guide to Artificial Intelligence This book helps individuals familiarize themselves with the most popular machine learning (ML) algorithms and delves into the details of deep learning, covering topics like CNN, RNN, etc. It is a beginner-friendly guide and a good starting point for people new to this field.

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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. TensorFlow Developer Professional Certificate This course teaches how to build and train neural networks using TensorFlow through a hands-on program.

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Towards AI

MAY 10, 2024

Speech-to-text with a neural network running locallyImage by Mark Anderson If you’ve watched the Iron Man movies, you’re well aware of the how helpful Jarvis can be. This is known as speech to text and is something I will try and re-create in this post using python and a bit of machine learning.

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AssemblyAI

AUGUST 15, 2023

In this tutorial, we will learn how to use LLMs to automatically summarize audio and video files with Python. We’ll use the AssemblyAI Python SDK in this tutorial. python -m venv transcriber # you may have to use `python3` Activate the virtual environment with the activation script on macOS or Linux: source.

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Marktechpost

JULY 28, 2024

Trace treats the computational workflow as a graph, similar to neural networks, and optimizes heterogeneous parameters using Optimization with Trace Oracle (OPTO). The LLM-based optimization algorithm OptoPrime is designed for the OPTO problem. Trace feedback is a pseudo-algorithm, allowing the LLM to suggest parameter updates.

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Unite.AI

AUGUST 27, 2024

C++, Python, Java, and Rust each have distinct strengths and characteristics that can significantly influence the outcome. Python Guido van Rossum developed Python in the late 1980s, emphasizing simplicity and readability. Python's framework is built to simplify AI development, making it accessible to both beginners and experts.

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Marktechpost

JULY 23, 2023

One key area of development is deep learning, where neural networks are trained on huge datasets of images to recognize and classify objects, scenes, and events. In the latest innovation, Jalali-Lab @ UCLA has developed a new Python library called PhyCV, which is the first Physics-based Computer vision Python library.

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Marktechpost

DECEMBER 27, 2023

Additionally, PostgresML supports the training of tabular data on more than 50 algorithms, including popular ones like random forests and neural networks. It also allows managing open-source ML models from platforms like HuggingFace, providing a convenient way to track experiment results.

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Pickl AI

AUGUST 14, 2024

Summary: Neural networks are a key technique in Machine Learning, inspired by the human brain. Different types of neural networks, such as feedforward, convolutional, and recurrent networks, are designed for specific tasks like image recognition, Natural Language Processing, and sequence modelling.

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Marktechpost

JUNE 3, 2024

Introduction to Machine Learning This course covers machine learning basics, including problem-solving, model building, and key algorithms. The course spans eight weeks, with lectures and Python exercises. Students will learn to derive detection models, handle various data types, and implement models using Python labs.

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Marktechpost

NOVEMBER 11, 2024

Python has become the go-to language for data analysis due to its elegant syntax, rich ecosystem, and abundance of powerful libraries. Data scientists and analysts leverage Python to perform tasks ranging from data wrangling to machine learning and data visualization. NumPy NumPy is the cornerstone of numerical computing in Python.

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Marktechpost

JUNE 28, 2024

Python: Advanced Guide to Artificial Intelligence This book helps individuals familiarize themselves with the most popular machine learning (ML) algorithms and delves into the details of deep learning, covering topics like CNN, RNN, etc. It is a beginner-friendly guide and a good starting point for people new to this field.

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Pickl AI

SEPTEMBER 3, 2024

Summary: Artificial Neural Network (ANNs) are computational models inspired by the human brain, enabling machines to learn from data. Introduction Artificial Neural Network (ANNs) have emerged as a cornerstone of Artificial Intelligence and Machine Learning , revolutionising how computers process information and learn from data.

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Unite.AI

DECEMBER 11, 2023

Gemini's capabilities : Spatial Reasoning ( Source ) Gemini's capabilities extend to executing programming tasks( Source ) Gemini sophisticated design is based on a rich history of neural network research and leverages Google’s cutting-edge TPU technology for training. In coding benchmarks, with Gemini Ultra attaining a score of 74.4%

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IBM Journey to AI blog

DECEMBER 15, 2023

When AI algorithms, pre-trained models, and data sets are available for public use and experimentation, creative AI applications emerge as a community of volunteer enthusiasts builds upon existing work and accelerates the development of practical AI solutions. Morgan’s Athena uses Python-based open-source AI to innovate risk management.

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Marktechpost

APRIL 24, 2024

The increasing complexity of AI systems, particularly with the rise of opaque models like Deep Neural Networks (DNNs), has highlighted the need for transparency in decision-making processes. Moreover, it can compute these contribution scores efficiently in just one backward pass through the network. Image Source 10.

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Marktechpost

MARCH 31, 2024

The book covers topics like supervised learning, unsupervised learning, neural networks, support vector machines, etc. It covers topics like calculus, probability, linear algebra, and statistics and how to apply them to algorithms like linear regression and logistic regression.

Data Science 122

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Unite.AI

AUGUST 28, 2023

Traditional Computing Systems : From basic computing algorithms, the journey began. Neural Networks & Deep Learning : Neural networks marked a turning point, mimicking human brain functions and evolving through experience. Running Code : Beyond generating code, Auto-GPT can execute both shell and Python codes.

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Marktechpost

NOVEMBER 16, 2024

Python: Advanced Guide to Artificial Intelligence This book helps individuals familiarize themselves with the most popular machine learning (ML) algorithms and delves into the details of deep learning, covering topics like CNN, RNN, etc. It is a beginner-friendly guide and a good starting point for people new to this field.

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Bugra Akyildiz

FEBRUARY 3, 2024

SMAD traditionally relies on hand-crafted features and statistical models, but Netflix in this post how they leverage deep learning , particularly convolutional neural networks (CNNs) , for superior performance and generalizability. Libraries AutoRound is an advanced weight-only quantization algorithm, based on SignRound.

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