# Rapid Duck **Main Questions to be addressed:** * What is it? * When did they start? * Which company initiated it? * What are the top 5 pros and cons? ## # RD12001 Search on ML Tools **Participants:** * Eswar * Bairavi * Charles Duration: 30 minutes ``` MLTools 101: Knime Knative Streamlit alternatives: Gradio Plotly Dash API Bokeh Shiny Jupyter MLflow start Gradio Pycaret Weights and biases https://wandb.ai/site Neptune Data versioning experiment tracking Interface monitoring Can be integrated with MLFlow DVC ML Pytorch lightning Top 20 Pytorch libraries Top 10 Tensorflow libraries https://www.tensorflow.org/resources/libraries-extensions Tensorflow Hub Model Optimization Tensorflow Recommenders Lattice Tensorflow Graphics Tensorflow Federated Probability Tensor2Tensor Tensorflow Privacy Tensorflow Agents Dopamine TRFL Mesh Tensorflow RaggedTensors UnicodeOps Tensorflow Ranking Magenta Nucleas Sonnet Neutral Structured Learning Tensorflow Addon Tensorflow I/O Tensorflow Quantum Model Cart Toolkit Model Remediation Fairness Indicators Cloud Decision Forests Tensorflow Text https://www.tensorflow.org/text DVC alternative: Dolthub DeltaLake Git Large File Storage PachyDerms Dolt LakeFS ML Image Classifier Chatistics ``` --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://tactlabs.gitbook.io/featurepreneur/rapid-duck.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.