Do Simpler Machine Learning Models Exist and How Can We Find Them?
The above is the title of a talk by computer scientist Cynthia Rudin. here’s the abstract:
Read more »An analysis of the limits of scaling datasets in Machine Learning
We analyze the growth of dataset sizes used in machine learning for natural language processing and computer vision, and extrapolate these using two methods; using the historical growth rate and estimating the compute-optimal dataset size for future predi…
Read more »Video Transcription with Serverless Machine Learning (Modal)
Contribute to elanmart/cbp-translate development by creating an account on GitHub.
Read more »Machine Learning Students Overfit to Overfitting
Overfitting and generalization is an important concept in Machine Learning as only models that generalize are interesting for general applications. Yet some students have trouble learning this important concept through lectures and exercises. In this pape…
Read more »Audio Signal Processing for Machine Learning [video]
Master key audio signal processing concepts. Learn how to process raw audio data to power your audio-driven AI applications.
Read more »Sematic (YC S22) Seed Stories – Open-Source Continuous Machine Learning Platform
On today’s episode of Seed Stories, I had a chance to sit down with Emmanuel Turlay founder and CEO of Sematic https://www.sematic.dev By using Sematic, deve…
Read more »List for Lego Machine Learning
Contribute to 360er0/awesome-lego-machine-learning development by creating an account on GitHub.
Read more »Homemade Machine Learning
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained – GitHub – trekhleb/homemade-machine-learning: 🤖 Python examples of popular machine …
Read more »Automating API Creation in Machine Learning with Docker
Pipeline is an open source API for building AI/ML workflows – pipeline/examples/docker at main · mystic-ai/pipeline…
Read more »A Survey on Machine Learning Techniques for Source Code Analysis
The advancements in machine learning techniques have encouraged researchers to apply these techniques to a myriad of software engineering tasks that use source code analysis, such as testing and vulnerability detection. Such a large number of studies hind…
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