Programmers_guide_to_Python
MLflow
Programmers_guide_to_Python | MLflow | |
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11 | 56 | |
173 | 17,335 | |
- | 1.5% | |
4.7 | 9.9 | |
over 2 years ago | 3 days ago | |
Python | ||
Creative Commons Attribution Share Alike 4.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Programmers_guide_to_Python
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Programmer's guide to Python website
Hello everyone, I have created a website for my ebook Programmer's guide to Python. On github it wasn't easy to read due to the size, so I thought a website could be more convenient. I've considered topics which are important and which should cover most grounds in Python programming and more. My goal was to create a concise and easy to follow guide to Python programming. I am looking forward to add more content like testing and some standard libraries that we use most often. Let me know your thoughts, suggestions or improvements regarding the website or contents, anything that needs to be added or something else. The current plain learning path will stay forever free and will have no ads, the interactive mode is currently slowly under works, and so I am not much sure about it yet. Hope you find it useful, you can access the website here.
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Just bought Angela Yu’s 100 day Python course!
You can also use my book to fine tune your learning. It's free and I keep updating it, so I hope it helps.
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Any of the current programming/coding bundles worth buying if the intend is to learn Python ( I have very minor previous programming experience)
Try my book once you're done with the basics.
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[Repost] Learn enough python with Programmer's guide to Python
Hello everyone, I have written a e-book named "Programmer's guide to Python", this is the second time I am making a post about it. It is designed to learn python fast by going through concepts with examples, with easy language and straightforward explanations. Only prerequisite is that you should have some basic exposure to programming. It covers most of the hot/necessary topics and more. It's a free book that you access right here on my github. I have recently worked alot and have updated alot inside out, fixing mistakes/errors, adding topics. I think the book is ready to ~90%, probably more, I'll drop the pdf version once ready. The thing is I don't have any reviewer to review it yet, so if anyone with enough experience who would like to collaborate, fix somethings, review or anything let me know, I'll add you to the contribution/reviewer list or maybe as a co-author if you put up enough work. Finally if you'll be reading it, I would like to know your thoughts/suggestions on improvements and maybe something you'd liked to be added in future. That's it, I hope this book helps you in learning python 🙌.
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Old guy programmer here, need to brush up on Python quickly!
You can try reading my book, let me know your thoughts.
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Programmer's guide to Python, learn almost everything in python.
Hello everyone, I hope you're doing fine, I recently wrote Programmer's guide to Python, its a book to learn python fast. If you have prior programming knowledge and are looking to learn python, this will help you kickstart your learning. If you have previously taken basic python courses and want to solidify your learning, this is for you too. It's short, fast and free. It is designed to cover all the important aspects of python, just good enough get you building stuff with Python. I hope it benefits you in learning python. Let me know your thoughts.
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Just finished a beginners python course, what next?
Well you can use my Programmer's guide to Python to solidify your learning. I recently wrote it, it's fast and short way to learn python. I also have ml recommendations which I have curated, they are all almost free and not affiliated. Take a look here, happy learning.
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Need Help finding a beginner friendly course for Python that provides an E-certificate
You can find some resources here they are all almost free and not affiliated. I recently wrote Programmer's guide to Python which is short and fast way to learn python, also free. Do take a look.
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I've learned a little bit of python. Now what?
You can use my Programmer's guide to Python to strengthen your python knowledge. Please take a look.
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Best resources for learning Python
Programmer's guide to Python
MLflow
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Observations on MLOps–A Fragmented Mosaic of Mismatched Expectations
How can this be? The current state of practice in AI/ML work requires adaptivity, which is uncommon in classical computational fields. There are myriad tools that capture the work across the many instances of the AI/ML lifecycle. The idea that any one tool could sufficiently capture the dynamic work is unrealistic. Take, for example, an experiment tracking tool like W&B or MLFlow; some form of experiment tracking is necessary in typical model training lifecycles. Such a tool requires some notion of a dataset. However, a tool focusing on experiment tracking is orthogonal to the needs of analyzing model performance at the data sample level, which is critical to understanding the failure modes of models. The way one does this depends on the type of data and the AI/ML task at hand. In other words, MLOps is inherently an intricate mosaic, as the capabilities and best practices of AI/ML work evolve.
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My Favorite DevTools to Build AI/ML Applications!
MLflow is an open-source platform for managing the end-to-end machine learning lifecycle. It includes features for experiment tracking, model versioning, and deployment, enabling developers to track and compare experiments, package models into reproducible runs, and manage model deployment across multiple environments.
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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.
What are some alternatives?
Python Cheatsheet - All-inclusive Python cheatsheet
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
python-cookbook - Code samples from the "Python Cookbook, 3rd Edition", published by O'Reilly & Associates, May, 2013.
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
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.
neptune-client - 📘 The MLOps stack component for experiment tracking
dagster - An orchestration platform for the development, production, and observation of data assets.