お仕事の依頼、料金、その他お問い合わせはこちらからお願い致します。 技術顧問 内容 技術戦略の策定：企業のビジネス目標と一致するような技術戦略の立案を支援します。 技術アーキテクチャの設計：システムや製品の開発において適切な技術アーキテクチャの実現を支援します。 技術評価：新しい技術やツールの導入が適切かどうかを判断し…

Build better ML models using feature exploration techniques for feature understanding, noisy/leaky feature detection and feature debugging.

This is the latest issue of my newsletter. Each week I cover the latest research and perspectives on developer productivity.

Full coding of Stable Diffusion from scratch, with full explanation, including explanation of the mathematics. Visual explanation of text-to-image, image-to-...

This is the latest issue of my newsletter. Each week I cover the latest research and perspectives on developer productivity.

I’m happy to announce ReviewNB, a tool for version controlling Jupyter Notebooks. You can see visual diff for Jupyter notebooks on…

The second edition of Deep Learning Interviews is home to hundreds of fully-solved problems, from a wide range of key topics in AI. It is designed to both rehearse interview or exam specific...

We share five steps on approaching machine learning from a business perspective that helped to build and scale our suite of machine learning products.

Last year, Databricks launched MLflow, an open source framework to manage the machine learning lifecycle that works with any ML library to simplify ML engine...

As ML matures from research to applied business solutions, so do we need to improve the maturity of its operation processes.

We expanded speech technology from about 100 languages to over 1,000 by building a single multilingual speech recognition model supporting over 1,100 languages.

If you’ve tried your hand at machine learning or data science, you know that code can get messy, quickly. 

In this tutorial we learn to quickly train Huggingface BERT using PyTorch Lightning for transfer learning on any NLP task

Style guides for Google-originated open-source projects

Predictive modeling with deep learning is a skill that modern developers need to know. PyTorch is the premier open-source deep learning framework developed and maintained by Facebook. At its core,...

A tried and tested approach to structuring ML projects

Evals, RAG, fine-tuning, caching, guardrails, defensive UX, and collecting user feedback.

I want to provide some tips from my experience implementing a paper. I'm going to cover my tips so far from implementing a dramatically scaled-down versio...

by Roger Menezes, Rahul Jha, Gary Yeh, and Sudarshan Lamkhede

Many production machine learning challenges are paralleled in software engineering

どうも緒方@conta_です。 みなさんAI頑張ってますか？ きっと昼はGPUサーバーを回して、夜は結果待ちでビールサーバーを回してる人が多いことでしょう。 機械学習を実際のプロダクトに活用する場合、自分が解きたいタスクがそのままオープンなデータセットで解決できることは少ないので、まず最初に課題となるのはデータセット作…

In this post, we dive deeper into each of the GPU-accelerated indexes mentioned in part 1 and give a brief explanation of how the algorithms work, along with a summary of important parameters to fine…

最高の脳で働く方法 Your Brain at Work

Full Stack Deep Learning course covers the full stack for building ML-powered products.

In this post, we elucidate the simple yet powerful idea of combining user profiles and item attributes to generate personalized content recommendations using LLMs. As demonstrated throughout the...

Given a long list of anomaly detection algorithms developed in the last few decades, how do they perform with regard to (i) varying levels of supervision, (ii) different types of anomalies, and...

「技術的負債に向き合う Online Conference」 2023/11/21 の発表資料です。 https://findy.connpass.com/event/297813/

In this article, we are going to understand how self-attention works from scratch. This means we will code it ourselves one step at a time. Since its introdu...

A Summary of Techniques and Approaches for Responsible AI

LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models (LLMs).

This is a 1 hour general-audience introduction to Large Language Models: the core technical component behind systems like ChatGPT, Claude, and Bard. What the...

A practical approach to versioning machine learning projects using Git Branches that simplifies workflows and organises data and models

The official GitHub page for the survey paper "A Survey on Evaluation of Large Language Models". - MLGroupJLU/LLM-eval-survey

What is RAG ?

List of awesome mlops articles. Curated from Feb 2022. - keigohtr/state-of-mlops

At Uber, millions of machine learning (ML) predictions are made every second, and hundreds of applied scientists, engineers, product managers, and researchers work on ML solutions daily. Uber wins by...

LangChain simplifies building AI assistants with large language models, providing an intuitive API, memory capabilities, access to external tools, the ability to chain LLM actions, and prompt...

Learn how to design systems at scale and prepare for system design interviews

Technical and architectural details of how we synced and embedded 1 billion vectors for a RAG workflow

The 2022 McKinsey Global Survey on AI shows the expansion of the technology’s business adoption over the last five years and provides insights on tech talent.

AI Observability & Evaluation. Contribute to Arize-ai/phoenix development by creating an account on GitHub.

CCSE 2019登壇 https://ccse.jp/2019/

Being able to work with multimodal data is essential for AI to operate in the real world. This post gives an overview of multimodality and goes into detail about how to train a multimodal system,...

Introduction

An end-to-end implementation of intent prediction with Metaflow and other cool tools - jacopotagliabue/you-dont-need-a-bigger-boat

To set some context, I would like to mention “T-shaped” engineering skills.

This article focuses on improving the modeling performance of LLMs by finetuning them using carefully curated datasets. Specifically, this article highlights...

We summarise the state of the competitive landscape and analyse the 200+ competitions that took place in 2022. Plus a deep dive analysis of 67 winning solutions to figure out the best strategies to...

Data preparation and modeling work for some, and implementation/lifecycle support for others are some of the tasks they must perform.

The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch. - GitHub - ritchieng/the-incredible-pytorch: The Incredible PyTorch: a curated list...

An Open Source, Self-Hosted Platform For Applied Deep Learning Development - dessa-oss/atlas

For the past several years, I’ve run a learning circle with engineering executives. The most frequent topic that comes up is career management–what should I do next? The second most frequent topic is...

2020年5月18日からTRI-AD (Toyota Research Institute - Advanced Development, Inc.) にSenior Engineerとして入社しました。所属はMLToolsという部署で、社内の機械学習エンジニア向けにMLOpsの基盤を提供しています。試用期間の３ヶ月が…

Deploying Models Into Production Is A Complex Affair

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production. - eugeneyan/applied-ml

Explanation to key concepts in ML. Contribute to dair-ai/ML-Papers-Explained development by creating an account on GitHub.

A professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc for Out-of-distribution detection, robustness, and generalization - huytransformer/Awesome-...

MLCT #12 https://mlct.connpass.com/event/172550/

In early 2022, Lyft already had a comprehensive Machine Learning Platform called LyftLearn composed of model serving, training, CI/CD…

Machine learning techniques often fail or give misleadingly optimistic performance on classification datasets with an imbalanced class distribution. The reason is that many machine learning algorit...

Uber has been one of the most active contributors to open source machine learning technologies in the last few years. While companies like…

Learn about ML serving platforms that serve hundreds to thousands of models.