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You've taken the course in the ML about neural nets. You start to build a project. And the question is how to select the best neural network architecture? Neural Architecture Sea...
.@h2oai = one of the most widely adopted ML platforms in the enterprise space. H2O AutoML is a recent addition to the stack that enables the automation of ML workflows in the Aut...
1) What is population-based training (PBT)? 2) How to use PBT in hyperparameter optimization? 3) How PBT helped in the creation of self-driving car models? 3 Answers are hereπ htt...
π₯2 New Super Models to Handle Any Type of Dataset We build models optimized for a specific type of dataset like: - text - audio - computer vision - etc. Is it possible to create...
π€@huggingface Transformer library is one of the few frameworks that includes transformer models for computer vision.β¬οΈ https://t.co/M2Gz5pNXh7
.@OpenAI ImageGPT is one of the first transformer architectures applied to computer vision scenarios.π https://t.co/1sVv21pj23
The field of computer vision has long been dominated by CNNs. But CNNs can be demanding from a computational standpoint. The attention mechanisms make transformers a strong candi...
Hyperparameters are numbers that the model cannot learn. So, you need to optimize them on your own. Finding the right hyperparameters is crucial for the viability of your ML model...
.@PrometheusIO is a widely-adopted technology stacks for capturing and storing large datasets. It's also a favorite infrastructure building blocks of ML engineering teams.β¬οΈ https...
You've trained a time-series forecasting model, and now you want to backtest it? Backtesting a real-world model is such a challenge. Fortunately, you can use frameworks built by...
Training intelligence agents to interact with physical environments is one of the most complex and expensive challenges. Why? Let's discuss that.β¬οΈ
The most famous transformer ever built. GPT-3. It established milestones in NLP that were impossible to even conceive of a few years ago.β¬οΈ