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Bringing ML practitioners together

Fully Connected is your home for curated tutorials, conversations with industry leaders, deep dives into the newest ML research, and a whole lot more.

FeaturedBlog PostsEventsGradient DissentForumComputer VisionNLPReinforcement LearningPyTorchKeras or TensorFlowfastaiHugging FaceScikitKaggleTwo Minute PapersReproducibility ChallengePaper OverviewVisualizationTutorialQuestionDiscussionResourcesShowcaseWebinarAMAPaper Reading GroupSalonfastbookCustom Charts
Pete Warden — Practical Applications of TinyML
Cayla Sharp, Angelica Pan
A Brief Introduction to Continual Learning
Shambhavi Mishra
iTAML: An Incremental Task-Agnostic Meta-learning Approach
Joel Joseph
Weights and Biases Raises $135m to Continue Building Our Developer-First MLOps Platform
Lukas Biewald
Meta-Consolidation for Continual Learning (MERLIN)
Shambhavi Mishra
Image-to-Image Translation Using CycleGAN and Pix2Pix
Ayush Chaurasia
Pivotal Tuning for Latent-Based Editing of Real Images
Sayantan Das
The Reality Behind Optimization of Imaginary Variables - II
Darshan Deshpande
Financial Sentiment Analysis on Stock Market Headlines With FinBERT & Hugging Face
Ivan Goncharov
Cross Entropy Loss: An Overview
Saurav Maheshkar
YOLOv5 Object Detection on Windows (Step-By-Step Tutorial)
Dave Davies
JSTASR: Joint Size and Transparency-Aware Snow Removal Algorithm
Kajal Puri
Uncertainty-Guided Continual Learning With Bayesian Neural Networks
Shravan Nayak
Backpropagated Gradient Representations for Anomaly Detection
Shambhavi Mishra
Chris Albon — ML Models and Infrastructure at Wikimedia
Cayla Sharp, Angelica Pan
Dynamic Convolution: Attention over Convolution Kernels (CVPR 2020)
Sachin Malhotra
Decision Trees: A Guide with Examples
Saurav Maheshkar
Hyperparameter Optimization for Hugging Face Transformers
Ayush Chaurasia
Dynamic Group Convolution for Accelerating Convolutional Neural Networks (ECCV 2020)
Sachin Malhotra
How to Use LSTMs in PyTorch
Saurav Maheshkar
Named Entity Recognition with W&B and spaCy
Stacey Svetlichnaya
Dynamic Convolutions: Exploiting Spatial Sparsity for Faster Inference (CVPR 2020)
Sachin Malhotra
Emily M. Bender — Language Models and Linguistics
Cayla Sharp, Angelica Pan
Hyperparameter Search with spaCy and Weights & Biases
Scott Condron
Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets (CVPR 2020)
Abhay Puri
Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification
Animesh Gupta
Tensorboard with Accelerators - A Guide
Saurav Maheshkar
Visualizing Prodigy Datasets Using W&B Tables
Kevin Shen
How to Compare Tables in Workspaces
Stacey Svetlichnaya
Bad Global Minima Exist and SGD Can Reach Them
Gustavo Sutter P. Carvalho, João Araújo, João Pedro Rodrigues Mattos, João Marcos Cardoso da Silva, Bruno Gomes Coelho
How Capella Space Produces World Class Satellite Data with the Help of Weights & Biases
Weights & Biases Case Studies
A Public Dissection of a PyTorch Training Step
Charles Frye
Text Classification With BERT
akshay uppal
Text Classification with AWS SageMaker, Hugging Face, and W&B
Morgan
Omnimatte: How to Detect Objects and Their Effects
Scott Condron
VIDEO: Teaching a Self-Driving RC Car To Obey the Law. And Then Break It.
Justin Tenuto
How to Fine-Tune Hugging Face Transformers with Weights & Biases
Ayush Thakur
When Does Self-Supervision Improve Few-Shot Learning?
Arjun Ashok, Haswanth Aekula
Meta Dropout: Learning to Perturb Latent Features for Better Generalization
Joel Joseph
Reproducible spaCy NLP Experiments with Weights & Biases
Scott Condron
SF-Net: Single-Frame Supervision for Temporal Action Localization
Kajal Puri
Using Artifacts to Build an End to End ML Pipeline
Armand du Parc Locmaria
Feedforward Networks for Image Classification
Saurav Maheshkar
Debugging a Self-Driving RC Car
Armand du Parc Locmaria
DALL·E mini
Boris Dayma, Suraj Patil, Pedro Cuenca, Khalid Saifullah, Tanishq Abraham, Phúc Lê, Luke, Ritobrata Ghosh
Speed, Scale and Simplicity: Weights & Biases Teams Up with NVIDIA to Accelerate Machine Learning
Lukas Biewald, Chris Van Pelt, Shawn Lewis
AlphaFold-ed Proteins in W&B Tables
Charles Frye, Stacey Svetlichnaya
Using AWS Sagemaker and Weights & Biases Together on Digit Recognition with MNIST
Costa Huang
Using W&B with DeepChem: Molecular Graph Convolutional Networks
Kevin Shen
Tables Tutorial: Recreating Whale Melodies on Orchestral Instruments
Stacey Svetlichnaya
DICOM Visualization with W&B Tables
Kevin Shen
SBX Robotics: Synthetic Training Data & Scene Composition with Tables
Artem @ SBX Robotics
Tables Tutorial: Visualize Text Data & Predictions
Stacey Svetlichnaya
Announcing W&B Tables: Iterate on Your Data
Shawn Lewis, Stacey Svetlichnaya, Tim Sweeney, Carey Phelps
The Geometry of Deep Generative Image Models
Sayantan Das
Is MLP-Mixer a CNN in Disguise?
Aman Arora
Bringing Back MLPs
Saurav Maheshkar
A Deep Dive into Neural Architecture Search Without Training (NASWOT)
Lukas Malik
MLPs are All You Need: Back to Square One?
Saurav Maheshkar
Introducing the pixel2style2pixel (pSp) Framework with W&B
Yuval Alaluf
How Gradio and W&B Work Beautifully Together
Abubakar Abid
Hugging Face Flax Community Week and W&B Support
Morgan
Training a Remote Controlled Car to Drive Itself
Justin Tenuto
AMA with Amanda Duarte, co-creator of the How2Sign Dataset
Charles Frye
Is ImageNet21k a Better Dataset for Transfer Learning in Steganalysis?
Yassine Yousfi
W&B Study Group: fastai w/ Hugging Face
Andrea Pessl
Inject Noise to Remove Noise: A Deep Dive into Score-Based Generative Modeling Techniques
Sayantan Das
Predicting Lung Disease with Binary Classification on the NIH Chest X-ray Dataset
Ayush Thakur
Gym-μRTS: Toward Affordable Deep Reinforcement Learning Research in Real-Time Strategy Games
Costa Huang, Chris Bamford
Fine-Grained Image Classification (FGIC) with B-CNNs
Rajesh Shreedhar Bhat, Souradip Chakraborty
The Reality Behind the Optimization of Imaginary Variables
Darshan Deshpande
Introducing Bag of Words: The W&B Newsletter
Justin Tenuto
Data Science Experiments Management with Weights & Biases
BroutonLab team
A Gentle Introduction To Weight Initialization for Neural Networks
Saurav Maheshkar
How Well Can a CNN Detect Architectural Style?
Mason Sanders
ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases
Aman Arora
Learn How Graphcore is Supporting the Next Generation of Big Models with the Help of W&B
Weights & Biases Case Studies
How Nanit Improves and Develops Models
Nimrod Shabtay
Funnel Activation for Visual Recognition (CVPR 2020)
Manoj Manjhari
Gated Channel Transformation for Visual Recognition (CVPR 2020)
Manoj Manjhari
An Introduction to Attention
Aritra Roy Gosthipaty, Devjyoti Chakraborty
Lyft's High-Capacity End-to-End Camera-Lidar Fusion for 3D Detection
Weights & Biases Case Studies
Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training (ECCV 2020)
Avantika
Sentiment Analysis with Bag of Tricks
Devjyoti Chakraborty, Piyush Thakur
Revisiting ResNets: Improved Training and Scaling Strategies
Aman Arora
Strip Pooling: Rethinking Spatial Pooling for Scene Parsing (CVPR 2020)
Manoj Manjhari
NeRF – Representing Scenes as Neural Radiance Fields for View Synthesis
Lavanya Shukla
Inside Hugging Face's Accelerate!
Aman Arora
Topological Autoencoders
Adrish Dey
Image Generation Based on Abstract Concepts Using CLIP + BigGAN
Hao Hao Tan
On the Relationship Between Self-Attention and Convolutional Layers
Nishant Prabhu, Mukund Varma T
What Do Compressed Deep Neural Networks Forget?
Saurav Maheshkar
Object Detection with YOLO and Weights & Biases
Ayush Chaurasia
Visualise Failure - Debugging with Model Activations
Morgan
One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing
Ayush Thakur
Rigging the Lottery: Making All Tickets Winners
Rajat Vadiraj Dwaraknath, Varun Sundar
Exploring Adaptive Gradient Clipping and NFNets
Ayush Thakur
Getting Started with Numerai Signals: Sentiment Analysis
Carlo Lepelaars
Tables Tutorial: Visualize Data for Image Classification
Stacey Svetlichnaya
Understanding what works (and why) in Deep Metric Learning
Karsten Roth
The Science of Debugging with W&B Reports
Sarah Jane
The W&B Machine Learning Visualization IDE
Shawn Lewis, Carey Phelps, Stacey Svetlichnaya, John Qian, Kyle Goyette, Tom Holmes
Generating Digital Painting Lighting Effects via RGB-space Geometry
Ayush Thakur
Using SimpleTransformers for Common NLP Applications
Ayush Chaurasia