Planet SciPy

Python posts posts by SciPy.

• Definite Guide to Building a Machine Learning Platform
• Managing Dataset Versions in Long-Term ML Projects
• How to Build a CI/CD MLOps Pipeline [Case Study]
• Comparing Tools For Data Processing Pipelines
• How Did We Get to ML Model Reproducibility
• Complete Guide to Visual ChatGPT
• ChatGPT: AI-Assisted Writing Pros, Cons, and Tips to 3x Content Production
• snakemake for doing bioinformatics - using wildcards to generalize your rules
• ChatGPT: Is Adding AI Writers To Your Content Production Process Worth It?
• Saving Utility Companies Years with Computer Vision
• Distributed Training: Errors to Avoid
• Managing Computer Vision Projects with Michał Tadeusiak
• Upcoming Release(s): Anaconda Distribution 2023.03 and Beyond
• Four Open-Source Projects and the Anaconda Maintainers Who Love Them
• conda & mamba on shared clusters works better now!
• Code in the Cloud With Anaconda—for Free!
• Training Models on Streaming Data [Practical Guide]
• Take Our OSS Security Survey!
• A brief overview of automation and parallelization options in UNIX/on an HPC
• Top 10 AI Platform Use Cases For the Enterprise
• Building a Sentiment Classification System With BERT Embeddings: Lessons Learned
• MLOps Is an Extension of DevOps. Not a Fork — My Thoughts on THE MLOPS Paper as an MLOps Startup CEO
• How to Version Control Data in ML for Various Data Sources
• snakemake for doing bioinformatics - a beginner's guide (part 2)
• Model Monitoring for Time Series
• snakemake for doing bioinformatics - a beginner's guide (part 1)
• sourmash has a plugin interface!
• Anaconda Unaffected by PyTorch Security Incident
• New Year, New You: What Will You Learn Next?
• Reading "Orwell's Roses" by Rebecca Solnit
• 2022: An Anaconda Year in Review
• A obsolescência humana na novela
• Speed Trap
• ChatGPT-4 Is a Smart Analyst, Unlike GPT-3.5
• Improvements to the Spyder IDE installation experience
• Interview with Meekail Zain, scikit-learn Team Member
• Introducing the Spyder-Watchlist plugin
• Por que abandonamos os blogs?
• Pandas DataFrame Output for sklearn Transformers
• The Russian Roulette: An Unbiased Estimator of the Limit
• scikit-learn and Hugging Face join forces
• So! You want to search all the public metagenomes with a genome sequence!
• Notes on the Frank-Wolfe Algorithm, Part III: backtracking line-search
• scikit-learn Sprint in Salta, Argentina
• New 2022 roadmap and grant funding
• Pollution in India : Real-time AQI Data
• My Mayavi story: discovering open source communities
• Pointwise mutual information (PMI) in NLP
• How to import your data into Acoular
• Checking for accessibility: thoughts and a checklist!
• On the Link Between Optimization and Polynomials, Part 5
• Announcing ribbity - a hacky project to build Web sites from GitHub issue trackers
• Interview with Norbert Preining, scikit-learn Team Member
• The Value of Open Source Sprints, the scikit-learn Experience
• 5 Years, 10 Sprints, A scikit-learn Open Source Journey
• Only size-1 arrays can be converted to Python scalars
• Interview with Lucy Liu, scikit-learn Team Member
• The second Common Fund Data Ecosystem hackathon - May 9-13, 2022!
• Storing 64-bit unsigned integers in SQLite databases, for fun and profit
• Interview with Maren Westermann: Extending the Impact of the scikit-learn Sprints to the Community
• Behind the Scenes of Data Umbrella scikit-learn Open Source Sprints
• The First Common Fund Data Ecosystem Hackathon
• Mestrado em Ciência da Computação 2022: Metaheurísticas
• DiffCast: Hands-free Python Screencast Creator — Create reproducible programming screencasts without typos or edits
• On minimum metagenome covers, and calculating them for your own data.
• Optimization Nuggets: Implicit Bias of Gradient-based Methods
• Optimization Nuggets: Exponential Convergence of SGD
• A bioinformatics training career panel in the DIB Lab
• Hiring an engineer and post-doc to simplify data science on dirty data
• TorchVision Datasets: Getting Started
• NumPy Any: Understanding np.any()
• PyTorch DataLoader Quick Start
• How the NumPy append operation works
• Hiring someone to develop scikit-learn community and industry partners
• Using snakemake to do simple wildcard operations on many, many, many files
• A paper on the Lees-Edwards method
• A biotech career panel in the DIB Lab
• Scaling sourmash to millions of samples
• Poetry for Package Management in Machine Learning Projects
• Development containers in VS Code: a quick start guide
• New sourmash databases are available!
• Colunando no O Estado do Piauí
• Ciclo de Entrevistas sobre as Pesquisas no PPGCC da UFPA – Inteligência Computacional
• Moving sourmash towards more community engagement - a funding application
• Searching all public metagenomes with sourmash
• Is your software ready for the Journal of Open Source Software?
• sourmash 4.1.0 released!!
• Basic Counting in Python
• How to Use the PyTorch Sigmoid Operation
• On the Link Between Optimization and Polynomials, Part 4
• NumFOCUS Welcomes Tesco Technology to Corporate Sponsors
• Job Posting | Communications and Marketing Manager
• Getting started with Acoular - Part 2
• Getting started with Acoular - Part 3
• Getting started with Acoular - Part 1
• sourmash 4.0 is now available! Low low cost if you buy now!
• On the Link Between Optimization and Polynomials, Part 3
• Introducing PyMC Labs: Saving the World with Bayesian Modeling
• Using MicroPython and uploading libraries on Raspberry Pi Pico — Using rshell to upload custom code
• sourmash v4.0.0 release candidate 1 is now available for comment!