Machine learning
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
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During debugging I've seen many constructs like list(map(lambda i: torch.device('cuda:' + str(i)), gpus))
I'd propose to replace those by "regular" list comprehensions. So the above is equivalent to [torch.device('cuda:' + str(i)) for i in gpus]
This replacement can be automated via regexp replacement for (likely) almost all cases.
Reasoning: The nesting of parentheses and the inline
Describe the issue linked to the documentation
In the section "Pull Request Checklist", this is how the text appears
A moderate use of type annotations is encouraged but is not mandatory. See [mypy quickstart](https://mypy.readthedocs.io/en/latest/getting_started.html) for an introduction, as well as [pandas contributing documentation]( https://pandas.pydata.org/pandas-docs/stabl
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
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Tesseract Open Source OCR Engine (main repository)
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The world's simplest facial recognition api for Python and the command line
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Deepfakes Software For All
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Caffe: a fast open framework for deep learning.
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100 Days of ML Coding
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Recent discussions on Discourse suggest that not all users know about apropos (or equivalently, using ?"..." for text search). The startup message currently mentions
Type "?" for help, "]?" for Pkg help.
I suggest that text search is added to this, but I am still looking for a compact way of phrasing it.
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
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A complete daily plan for studying to become a machine learning engineer.
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The most cited deep learning papers
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A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
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Currently, the C++ compiler generates lots of warnings: https://xgboost-ci.net/blue/organizations/jenkins/xgboost/detail/master/516/pipeline/61. It would be great to reduce the number of warnings.
Note to new contributors: Post a comment here if you'd like to work on this issue. Feel free to ping me for help.
The fastai deep learning library, plus lessons and tutorials
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Oct 19, 2020 - Jupyter Notebook
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
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《动手学深度学习》:面向中文读者、能运行、可讨论。英文版即伯克利“深度学习导论”教材。
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Oct 18, 2020 - Python
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
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Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
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Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
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Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
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Sep 8, 2020 - C++
A curated list of awesome Deep Learning tutorials, projects and communities.
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Oct 15, 2020
100-Days-Of-ML-Code中文版
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Feb 18, 2020 - Jupyter Notebook
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
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List of Computer Science courses with video lectures.
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