handson-ml2
MLflow
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handson-ml2 | MLflow | |
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12 | 54 | |
26,896 | 17,234 | |
- | 2.4% | |
0.0 | 9.9 | |
14 days ago | 3 days ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
handson-ml2
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Book recommendations for 18yo
A text on applied data science, if you like programming and diving into datasets, this could be a good thing to have, there's a pretty good one that's free on github here.
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Moving to TensorFlow from PyTorch
I'd recommend a skim through the Keras/TensorFlow portion of Hands-On-Machine-Learning-with-Scikit-Learn-Keras-and-Tensorflow (https://github.com/ageron/handson-ml2)
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Hands-on ML with Scikit-Learn, Keras and TF2 - Aurelien Geron (Details in comment)
Here's the GitHub repo for the 2nd Ed.
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It was exactly 2 years ago when I decided to self-study data analytics and now I accepted a 6-digit offer.
Hands-on machine learning (Python): Python reference for machine learning. Use their Github repo as a supplement because some codes in the book are outdated. Finish at least part 1: Fundamentals of machine learning.
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I want to relearn machine learning
You get access from the github, https://github.com/ageron/handson-ml2 Its free, but wont have much context without the book(also "free" at Libgen.is)
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Tensorflow error "W tensorflow/core/data/root_dataset.cc:163] Optimization loop failed: CANCELLED: Operation was cancelled"
Here is the repository.
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NLP resources
I remember an NLP course on DataCamp being helpful as an intro, but a resource I keep handy is Hands-On Machine Learning (Geron) which has really helpful follow along notebooks on the git. Then when you want some background: Deep Learning (Goodfellow)
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An OpenAI Gym docker that can render on Windows
example/18_reinforcement_learning.ipynb: This is a copy from Chapter 18 in Géron, Aurélien's book: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. Source code is here in GitHub.
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[D] Thoughts on Hands-On Machine Learning with Scikit-Learn, Keras & Tensorflow by Geron
Have you tried looking at the accompanying github repo.
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[D] Looking for good refreshers on stats / ML to go back to the ML engineer interview game after 2 years doing mostly Software.
Much of the material from that book is publicly available in this repo maintained by the author.
MLflow
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Platforms such as MLflow monitor the development stages of machine learning models. In parallel, Data Version Control (DVC) brings version control system-like functions to the realm of data sets and models.
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cascade alternatives - clearml and MLflow
3 projects | 1 Nov 2023
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EL5: Difference between OpenLLM, LangChain, MLFlow
MLFlow - http://mlflow.org
- Explain me how websites like Dall-E, chatgpt, thispersondoesntexit process the user data so quickly
- [D] What licensed software do you use for machine learning experimentation tracking?
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Exploring MLOps Tools and Frameworks: Enhancing Machine Learning Operations
MLflow:
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Options for configuration of python libraries - Stack Overflow
In search for a tool that needs comparable configuration I looked into mlflow and found this. https://github.com/mlflow/mlflow/blob/master/mlflow/environment_variables.py There they define a class _EnvironmentVariable and create many objects out of it, for any variable they need. The get method of this class is in principle a decorated os.getenv. Maybe that is something I can take as orientation.
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[D] Is there a tool to keep track of my ML experiments?
I have been using DVC and MLflow since then DVC had only data tracking and MLflow only model tracking. I can say both are awesome now and maybe the only factor I would like to mention is that IMO, MLflow is a bit harder to learn while DVC is just a git practically.
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[Q] Is there a tool to keep track of my ML experiments?
Hi, you should have a look at ML flow https://mlflow.org or weight and biases https://wandb.ai/site
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Looking for recommendations to monitor / detect data drifts over time
Dumb question, how does this lib compare to other libs like MLFlow, https://mlflow.org/?
What are some alternatives?
mit-deep-learning-book-pdf - MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
ggplot2-book - ggplot2: elegant graphics for data analysis
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
tests-as-linear - Common statistical tests are linear models (or: how to teach stats)
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
PythonDataScienceHandbook - Python Data Science Handbook: full text in Jupyter Notebooks
guildai - Experiment tracking, ML developer tools
dvc - 🦉 ML Experiments and Data Management with Git
tensorflow - An Open Source Machine Learning Framework for Everyone
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.