Synthetic Data Metrics: An #OpenSource #Python Library That Evaluates Synthetic #Data By Comparing It To The Real Data That You’re Trying To Mimic https://
bit.ly/3CJ64GC
#MachineLearning #DataScience #DataScientists #Analytics #BigData #AI #ML #NLP #TensorFlow #DEVCommunity
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Open Source Python Library for Synthetic Data Evaluation
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System of Constrained Policy Optimization in Machine Learning
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System of Constrained Policy Optimization. @rachelevagordon #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #GoLang #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
bit.ly/3hFaMNx -
Top 9 Face Detection Algorithms: Learn and Compare Guide
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No, It’s not Face Recognition, it’s Face Detection. Learn and compare among top 9 Face Detection algorithms.
— Satya Mallick (@LearnOpenCV) 12 novembre 2022
Head over to https://t.co/drkIRYRZTs to know more.#facedetection #computervision #ai #machinelearning #deeplearning #facedetection pic.twitter.com/SqIAIQ47TfNo, It’s not Face Recognition, it’s Face Detection. Learn and compare among top 9 Face Detection algorithms. Head over to https://
learnopencv.com/what-is-face-d
etection-the-ultimate-guide/
… to know more. #facedetection #computervision #ai #machinelearning #deeplearning #facedetection -
Computerphile: Essential Channel for Programmers
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Computerphile: Videos all about computers and computer stuff. Hands down, a must follow for every programmer!! Check this out
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Top 16 Python Projects in Machine Learning and Data Science
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Top 16 #Python projects #MachineLearning #DataScience #SQL #Cybersecurity #BigData #Analytics #AI #IIoT #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode #NodeJS #golang #NLP #GitHub #IoT #blockchain #DL
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Keras Preprocessing Layers: Seeking Company Collaboration for Large-Scale adapt()
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If you're a company that uses Keras and you face this use case (large scale adapt() of Keras preprocessing layers), would you consider working with us to implement it? We're a small team and we don't have the resources for this at this time…
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Beam-style computation support designed but not yet implemented
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Correct, the underlying API / infra is designed to potentially allow Beam-style computation. We have not implemented it and it's currently deprioritized (the current adapt() is serial and single-threaded). But we could if there's demand in the future — the design is there.
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TensorFlow Graph Performance Eliminates Python Slowness Issues
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The fact that we're able to do everything as part of the TF graph is really nice — Python slowness is never an issue. There's no need for us to rewrite anything in, like, Cython or Rust.
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Keras Preprocessing Layers: High-Performance In-Graph Implementation
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All the work is done in Keras preprocessing layers, which are implemented in TF ops (everything is 100% in-graph!) so it's highly performant. During training (presumably on GPU/TPU) you'd use async preprocessing in TF data to avoid CPU preprocessing being a bottleneck.
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Building Machine Learning Systems: Complete Components Overview
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Building machine learning systems is hard. Some of the components you need: 1. Data sources
2. Data pipelines
3. Feature stores
4. Model training
5. Model evaluation
6. Model deployment
7. Model monitoring
8. Predictions API At @abacusai we help you with this!