HyperLSTM PyTorch implementation https://t.co/c59I64qqGP
— /MachineLearning (@slashML) January 3, 2021
HyperLSTM PyTorch implementation https://t.co/c59I64qqGP
— /MachineLearning (@slashML) January 3, 2021
Compiling some resources for students next semester. Useful places for ML datasets:
— Sebastian Raschka (@rasbt) January 2, 2021
Tabular & cleaned:https://t.co/kcsoxPUYQG
By domain:https://t.co/fQ4KCuQuTZ
By application:https://t.co/veUoWTTu0O
Search engine:https://t.co/3ycpIQx71p
Community:https://t.co/Oa9miTVQYX
I updated my list of ML tools:
— Chip Huyen (@chipro) December 31, 2020
- 84 new tools (total 284) + interactive graph
- overview of MLOps landscape 2020
- ML tooling startups that have raised money in 2020. More than half are outside the Bay Area. Growing hubs: Boston, NYC, Tel Aviv.https://t.co/QTr7eJvP9l pic.twitter.com/64msYaBjGZ
Is it possible to do runtime type checking in python without mypy? Why, Yes! See fastcore.basics.typed
— Hamel Husain (@HamelHusain) December 23, 2020
🧵👇 pic.twitter.com/ZFN3XZIuiq
There are also several new tools for time series, i.e., the scikit-learn compatible sktime (https://t.co/XdV1RdQanq), its sktime-dl extension for DL and TensorFlow (https://t.co/UcRRxy2w0D), and pytorch-forecasting https://t.co/dtwVyx09Zu
— Sebastian Raschka (@rasbt) December 22, 2020
Currently toying around with *gradient checkpointing* to fit some of my larger DL models into VRAM. Such a simple an neat trick for more memory-efficient backpropagation. Great article here: https://t.co/yeHWZiSYYw. There's also a PyTorch implementation: https://t.co/uXz7C5vCdM pic.twitter.com/KM7wIOeEvb
— Sebastian Raschka (@rasbt) December 22, 2020
TabNet: Attentive Interpretable Tabular Learning
— ML Review (@ml_review) December 20, 2020
By @sercanarik @tomaspfister
Automates feature engineering for tabular models
Learns representations through unsupervised pre-training to predict masked features + supervised fine-tuning https://t.co/4xDY5O24tC pic.twitter.com/clKlkWH4sp
Excited to launch "ghapi" today in partnership with @GitHub. ghapi provides complete access to the entire GitHub API, using a consistent interface with many nice touches.
— Jeremy Howard (@jeremyphoward) December 18, 2020
See thread below for a demo and summary, or read the post for details: 1/https://t.co/DDzM6sm6Dw
🤗Transformers are starting to work with structured databases!
— Hugging Face (@huggingface) December 17, 2020
We just released 🤗Transformers v4.1.1 with TAPAS, a multi-modal model for question answering on tabular data from @googleAI.
Try it out through transformers or our inference API: https://t.co/cJWxi7mB68 pic.twitter.com/s0oU0UFwW8
⚡️ Slides from my super-speed-lightning talk: “What's new in dbplyr 2.0.0?” (the most important part, obvi, being @allison_horst's new logo)https://t.co/dLhheLcehK pic.twitter.com/FXT5glnSaC
— Mara Averick (@dataandme) December 15, 2020
pystiche is a PyTorch framework for Neural Style Transfer. It is one of the winners of 2019 PyTorch Summer Hackathon. Since then, it is peer-reviewed by pyOpenSci and published in the Journal of Open Source Software (JOSS). Learn more: https://t.co/L7KopmDVPA
— PyTorch (@PyTorch) December 14, 2020
Unwrap @RAPIDSai release 0.17 from our family to yours: #GPU-Accelerated TreeSHAP in @XGBoostProject. Decimal Types in cuDF. Datetime in cuXFilter. A podcast. And much more! Thanks for your support. Happy New Year! https://t.co/a9ZPIPAtjq
— RAPIDS AI (@RAPIDSai) December 14, 2020