Mlearning.ai

FEBRUARY 4, 2024

This is the second part of my Neural Networks 101 series, in this blog we are going to discuss about the training of machine learning models. Every day, I tweet about a variety of subjects here, such as software engineering, system design, deep learning, machine learning, and more. Here is a link where you can view it.

Neural Network 52

Neural Network Deep Learning Machine Learning Software Engineer 52

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).

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Neural Network Convolutional Neural Networks Machine Learning Data Scientist 52

OpenAI

JUNE 9, 2022

Large neural networks are at the core of many recent advances in AI, but training them is a difficult engineering and research challenge which requires orchestrating a cluster of GPUs to perform a single synchronized calculation.

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Neural Network Software Engineer AI AI 52

ODSC - Open Data Science

APRIL 1, 2025

Hybrid Text Classification: Labeling with LLMs and Dense Neural Networks Mohammad Soltanieh-ha, PhD, Clinical Assistant Professor at Boston University Reduce labeling costs without sacrificing accuracy. This hands-on session shows how to combine LLMs and neural networks for efficient, scalable text classification.

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Neural Network LLM Software Engineer AI 52

Marktechpost

APRIL 26, 2024

This limitation often affects their performance in complex software engineering tasks, such as program repair, where understanding the execution flow of a program is essential. Existing research in AI-driven software development includes several frameworks and models focused on enhancing code execution reasoning.

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Machine Learning Large Language Models Software Development Neural Network 140

AWS Machine Learning Blog

FEBRUARY 13, 2025

Language embeddings are high dimensional vectors that learn their relationships with each other through the training of a neural network. During training, the neural network is exposed to enormous amounts of text and learns patterns based on how words are colocated and relate to each other in different contexts.

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Neural Network Algorithm Software Engineer Categorization 95

Towards AI

AUGUST 24, 2023

Background As a professional AI engineer with 25+ years of software engineering experience, I have designed and implemented a wide variety of software applications and technologies. Therefore, I have used and implemented hundreds (perhaps thousands) of software libraries, frameworks, and APIs.

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Neural Network Software Engineer Algorithm Machine Learning 98

AWS Machine Learning Blog

NOVEMBER 26, 2024

Furthermore, you can use this diagram to ask follow-up questions: Why do we need a network load balancer in this architecture The following screenshot shows the response from the model. However, we’re not limited to using generative AI for only software engineering.

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LLM Convolutional Neural Networks Metadata Explainability 98

Mlearning.ai

JULY 20, 2023

In case you missed it, make sure you catch part 1 of this series- A Neuroscientists view into Improving Neural Networks - where we talked about the biological basis of bilaterality and how the asymmetric nature of our brains leads to greater performance. If any of you want to work on this, you know how to reach me. Simply put- yes.

Neural Network 52

Neural Network Machine Learning Convolutional Neural Networks Software Engineer 52

NVIDIA

DECEMBER 4, 2023

A RedHat software engineering team put it succinctly in a blog : “GPUs have become the foundation of artificial intelligence.” An AI model, also called a neural network, is essentially a mathematical lasagna, made from layer upon layer of linear algebra equations. The University of Toronto professor spread the word. “In

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Neural Network AI AI LLM 136

Unite.AI

AUGUST 22, 2023

We wrote developed custom rules (later more complex neural networks) to predict which customers we should approach with which products at which times to maximize the likelihood of a salesperson’s time resulting in revenue uplift. What was your favorite project and what did you learn from this experience?

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Big Data Neural Network Natural Language Processing Machine Learning 246

Marktechpost

JULY 28, 2024

In the past decade, the data-driven method utilizing deep neural networks has driven artificial intelligence success in various challenging applications across different fields. These models have great potential to understand, generate, and apply natural language.

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Data Analysis AI Modeling Data Science Artificial Intelligence 135

Marktechpost

APRIL 28, 2024

IBM AI Developer Professional Certificate This is a comprehensive course that introduces the fundamentals of software engineering and artificial intelligence and also covers some of the emerging technologies like generative AI. AI For Everyone “AI For Everyone” has been designed by DeepLearning.AI

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Artificial Intelligence Artificial Intelligence Prompt Engineering Prompt Engineer 108

Marktechpost

JULY 30, 2024

This innovative approach focuses on two key functions: decomposing state-of-the-art Graph Neural Networks (GNNs), LLMs, and Table Neural Networks (TNNs) into standardized modules, and enabling the construction of robust models through a “combine, align, and co-train” methodology.

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Large Language Models Neural Network Data Analysis Software Engineer 108

Towards AI

AUGUST 25, 2023

What is AI Engineering AI Engineering is a new discipline focused on developing tools, systems, and processes to enable the application of artificial intelligence in real-world contexts [1]. In a nutshell, AI Engineering is the application of software engineering best practices to the field of AI. Bourque and R.

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Machine Learning Software Engineer Neural Network Data Science 98

ODSC - Open Data Science

MARCH 12, 2025

AI engineering extended this by integrating AI systems more deeply into software engineering pipelines, making it a crucial field as AI applications became more sophisticated and embedded in real-world systems. Takeaway: The industrys focus has shifted from building models to making them robust, scalable, and maintainable.

Data Science 52

Data Science ETL Machine Learning AI Engineer 52

Flipboard

FEBRUARY 6, 2023

. “I realized that combining LLMs trained on code with my research on neural memory and reinforcement learning might allow us to build an AI software engineer that feels like a true colleague, not just a tool. This would be extraordinarily useful for companies and developers.”

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Software Engineer Neural Network Large Language Models Continuous Learning 123

Google Research AI blog

APRIL 25, 2023

Posted by Yicheng Fan and Dana Alon, Software Engineers, Google Research Every byte and every operation matters when trying to build a faster model, especially if the model is to run on-device. This simplified model illustrates a common approach for setting up search spaces. for the convolution layer.

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Neural Network Convolutional Neural Networks Algorithm Software Engineer 107

How to Learn Machine Learning

DECEMBER 15, 2024

In the rapidly evolving world of technology, machine learning has become an essential skill for aspiring data scientists, software engineers, and tech professionals. Coursera Machine Learning Courses are an exceptional array of courses that can transform your career and technical expertise. Why Coursera for Machine Learning?

Machine Learning 52

Machine Learning Neural Network Convolutional Neural Networks Software Engineer 52

Marktechpost

MARCH 26, 2024

Large language models (LLMs) have proven success in various tasks in the software engineering domain, such as generating code and documentation, translating code between programming languages, writing unit tests, and detecting and fixing bugs.

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Large Language Models Neural Network Software Engineer Machine Learning 99

Marktechpost

SEPTEMBER 11, 2024

The Problem of Learning Rate Scheduling The learning rate is one of the most crucial hyperparameters when training deep neural networks, especially LLMs. Despite the improvements made by earlier models, optimizing these hyperparameters remains a challenging task, especially when scaling to billions of parameters.

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Natural Language Processing Large Language Models Neural Network Software Engineer 121

Google Research AI blog

JUNE 14, 2023

Marcos Seefelder, Software Engineer, and Daniel Duckworth, Research Software Engineer, Google Research When choosing a venue, we often find ourselves with questions like the following: Does this restaurant have the right vibe for a date? Is there good outdoor seating? Are there enough screens to watch the game?

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Software Engineer Neural Network Computer Vision Metadata 129

IBM Journey to AI blog

JULY 6, 2023

Deep learning algorithms are neural networks modeled after the human brain. Machine learning engineers can specialize in natural language processing and computer vision, become software engineers focused on machine learning and more. Deep learning teaches computers to process data the way the human brain does.

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Data Science Machine Learning Big Data Data Mining 175

ODSC - Open Data Science

MARCH 28, 2023

The topics discussed will include TensorFlow, neural networks, PyTorch, autonomous machines, recommendation systems, reinforcement learning, and much more.

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Data Science Deep Learning Machine Learning Neural Network 92

AWS Machine Learning Blog

MARCH 13, 2025

MoE models like DeepSeek-V3 and Mixtral replace the standard feed-forward neural network in transformers with a set of parallel sub-networks called experts. He has over 20 years of experience as a full stack software engineer, and has spent the past 5 years at AWS focused on the field of machine learning.

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LLM Machine Learning AI AI 84

ODSC - Open Data Science

MARCH 13, 2023

Fan Staff Software Engineer | Quansight Labs As a maintainer for scikit-learn, an open-source machine learning library for Python, and skorch, a neural network library that wraps PyTorch, Thomas J. He also operates his own Python and data science consultancy and corporate training business.

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Data Science Deep Learning Machine Learning Software Engineer 80

AWS Machine Learning Blog

NOVEMBER 22, 2023

Similar to the rest of the industry, the advancements of accelerated hardware have allowed Amazon teams to pursue model architectures using neural networks and deep learning (DL). About the Authors Abhinandan Patni is a Senior Software Engineer at Amazon Search. Jerry Mannil is a software engineer at Amazon Search.

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LLM Software Engineer Auto-complete Neural Network 110

TheSequence

FEBRUARY 11, 2024

In this on-demand recording, Plaid Software Engineer Renault Young shared the technical challenges they faced, how they set up the data foundations they needed to start building an ML platform, what they used to look for patterns in transaction data in real time, and more. They are very impressive.

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LLM Neural Network ML Software Engineer 111

Dlabs.ai

DECEMBER 9, 2021

So if you’re somewhat familiar with neural networks, Python, PyTorch, or TensorFlow and you want to learn more about transformers, then this book is for you. Neural Network Methods in Natural Language Processing Author: Yoav Goldberg Yoav Goldberg’s primary goal is to elaborate on neural networks and their applications to NLP.

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Natural Language Processing Neural Network NLP Deep Learning 59

Google Research AI blog

JUNE 23, 2023

Posted by Ramki Gummadi, Software Engineer, Google and Kevin Chen, Software Engineer, YouTube Caching is a ubiquitous idea in computer science that significantly improves the performance of storage and retrieval systems by storing a subset of popular items closer to the client based on request patterns.

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Automation Neural Network Software Engineer Metadata 79

Pickl AI

JULY 14, 2023

Machine Learning and Neural Networks (1990s-2000s): Machine Learning (ML) became a focal point, enabling systems to learn from data and improve performance without explicit programming. Techniques such as decision trees, support vector machines, and neural networks gained popularity.

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Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

TensorFlow

NOVEMBER 29, 2023

Posted by Marat Dukhan and Frank Barchard, Software Engineers CPUs deliver the widest reach for ML inference and remain the default target for TensorFlow Lite.

Metadata 95

Metadata Neural Network Software Engineer Computer Vision 95

ODSC - Open Data Science

MARCH 27, 2023

Scaling AI/ML Workloads with Ray Kai Fricke | Senior Software Engineer | Anyscale Inc. If so, when and who should perform them? And, Most importantly, what is the point of all this governance, and how much is too much?

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Machine Learning Data Science Deep Learning Data Ingestion 98

Flipboard

JULY 31, 2023

Nowadays, with the advent of deep learning and convolutional neural networks, this process can be automated, allowing the model to learn the most relevant features directly from the data. a convolutional neural network), which then learns to map the features of each image to its correct label.

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Machine Learning Computer Vision Deep Learning Convolutional Neural Networks 123

AWS Machine Learning Blog

MARCH 30, 2023

The model extracts features from the image using a convolutional neural network. About the authors Jonathan Buck is a Software Engineer at Amazon Web Services working at the intersection of machine learning and distributed systems. As input, the model takes an image and a corresponding bounding box annotation.

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Machine Learning Convolutional Neural Networks Neural Network Computer Vision 93

Google Research AI blog

APRIL 14, 2023

Posted by Matthew Streeter, Software Engineer, Google Research Derivatives play a central role in optimization and machine learning. Our theory applies to elementary functions, such as exp and log , and common neural network activation functions, such as ReLU and Swish.

Neural Network 79

Neural Network Algorithm Machine Learning Software Engineer 79

TheSequence

OCTOBER 29, 2024

Previous architectures such as recurrent neural networks(RNNs)address some of these limitations but tend to forget information in long sequences and they are pretty hard to parallelize. It also reviews the SWE-Agent for software engineering tasks. This posses major scalability limitations for long context tasks.

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Neural Network Software Engineer LLM ML 59