How to use Google Speech to Text API to transcribe long audio files?
https://towardsdatascience.com/how-to-use-google-speech-to-text-api-to-transcribe-long-audio-files-1c886f4eb3e9?source=collection_home---4------0---------------------
https://towardsdatascience.com/how-to-use-google-speech-to-text-api-to-transcribe-long-audio-files-1c886f4eb3e9?source=collection_home---4------0---------------------
Towards Data Science
How to use Google Speech to Text API to transcribe long audio files?
Speech recognition is a fun task. A lot of API resources are available in market today which makes it easier for user to opt for one or…
Neural ODEs
Notebook here collects theory, basic implementation and some experiments of Neural Ordinary Differential Equations
https://github.com/urtrial/neural-ode
Link to NBViewer
https://nbviewer.jupyter.org/github/urtrial/neural_ode/blob/master/Neural%20ODEs%20(Russian).ipynb
Link to NBViewer (RUS)
https://nbviewer.jupyter.org/github/urtrial/neural_ode/blob/master/Neural%20ODEs.ipynb
Notebook here collects theory, basic implementation and some experiments of Neural Ordinary Differential Equations
https://github.com/urtrial/neural-ode
Link to NBViewer
https://nbviewer.jupyter.org/github/urtrial/neural_ode/blob/master/Neural%20ODEs%20(Russian).ipynb
Link to NBViewer (RUS)
https://nbviewer.jupyter.org/github/urtrial/neural_ode/blob/master/Neural%20ODEs.ipynb
GitHub
GitHub - msurtsukov/neural-ode: Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations - msurtsukov/neural-ode
The 10 coolest papers from CVPR 2018
The 2018 Conference on Computer Vision and Pattern Recognition (CVPR) took place last week in Salt Lake City, USA.
https://towardsdatascience.com/the-10-coolest-papers-from-cvpr-2018-11cb48585a49?source=collection_home---4------3---------------------
The 2018 Conference on Computer Vision and Pattern Recognition (CVPR) took place last week in Salt Lake City, USA.
https://towardsdatascience.com/the-10-coolest-papers-from-cvpr-2018-11cb48585a49?source=collection_home---4------3---------------------
Long-Range Robotic Navigation via Automated Reinforcement Learning
http://ai.googleblog.com/2019/02/long-range-robotic-navigation-via.html
http://ai.googleblog.com/2019/02/long-range-robotic-navigation-via.html
research.google
Long-Range Robotic Navigation via Automated Reinforcement Learning
Aleksandra Faust, Senior Research Scientist and Anthony Francis, Senior Software Engineer, Robotics at Google In the United States alone, there are...
PyTorch Machine Learning Tutorial - Machine Learning with Python and PyTorch
https://www.youtube.com/watch?v=TB-G1KqRb5o
https://www.youtube.com/watch?v=TB-G1KqRb5o
YouTube
PyTorch Python Tutorial | PyTorch Machine Learning Tutorial | Deep Learning Using PyTorch
Master Deep Learning and Computer Vision with PyTorch - Full Course on sale for $10! (normally $200):
https://www.udemy.com/pytorch-for-deep-learning-and-computer-vision/?couponCode=PYTORCHYOUTUBE09
PyTorch has rapidly become one of the most transformative…
https://www.udemy.com/pytorch-for-deep-learning-and-computer-vision/?couponCode=PYTORCHYOUTUBE09
PyTorch has rapidly become one of the most transformative…
Boosting: Is It Always The Best Option?
https://towardsdatascience.com/boosting-is-it-always-the-best-option-ce624a359c19
https://towardsdatascience.com/boosting-is-it-always-the-best-option-ce624a359c19
Medium
Boosting: Is It Always The Best Option?
Gradient boosting has become quite a popular technique in the area of machine learning. Given its reputation for achieving potentially…
Работа с Big Data в «МегаФон»
Директор по аналитике больших данных компании «МегаФон» рассказывает, как вырасти в профессионала в области big data и как именно работает с ними сотовый оператор.
https://www.youtube.com/watch?v=C6zSSWoOUOw«МегаФон»
Директор по аналитике больших данных компании «МегаФон» рассказывает, как вырасти в профессионала в области big data и как именно работает с ними сотовый оператор.
https://www.youtube.com/watch?v=C6zSSWoOUOw«МегаФон»
YouTube
МегаФон: как мы работаем с большими данными — OH, MY CODE #29
Директор по аналитике больших данных в «МегаФон» Виталий Щербаков рассказал о том, как происходит сбор и аналитика больших данных, как построить предсказательную модель поведения пользователей и как устроиться на работу в компанию. В конце ролика, по традиции…
Recurrent Neural Networks
Remembering what’s important
https://towardsdatascience.com/recurrent-neural-networks-d4642c9bc7ce
Remembering what’s important
https://towardsdatascience.com/recurrent-neural-networks-d4642c9bc7ce
Medium
Recurrent Neural Networks
Remembering what’s important
All the Steps to Build your first Image Classifier (with code)
From creating datasets to testing your program accuracy
https://medium.com/@artux51/all-the-steps-to-build-your-first-image-classifier-with-code-cf244b015799
From creating datasets to testing your program accuracy
https://medium.com/@artux51/all-the-steps-to-build-your-first-image-classifier-with-code-cf244b015799
Medium
All the Steps to Build your first Image Classifier (with code)
From creating datasets to testing your program accuracy
Probability Theory for Machine/Deep Learning
https://towardsdatascience.com/probability-theory-for-deep-learning-9551b9255cf0?source=collection_home---4------3---------------------
https://towardsdatascience.com/probability-theory-for-deep-learning-9551b9255cf0?source=collection_home---4------3---------------------
Medium
Probability Theory for Machine/Deep Learning
A very quick introduction to building a foundation in probability theory for understanding machine/deep learning
Как можно упростить и ускорить вычисление нейронной сети прямого распространения
https://habr.com/ru/hub/artificial_intelligence/
https://habr.com/ru/hub/artificial_intelligence/
Хабр
Искусственный интеллект — AI, ANN и иные формы искусственного разума / Хабр
Искусственный интеллект: как он есть и каким он должен быть.
По определению, к задачам искусственного интеллекта относятся все задачи, не имеющие точного алгоритмического решения.
Вот и давайте поговорим про нейронные сети, генетические алгоритмы, задачи…
По определению, к задачам искусственного интеллекта относятся все задачи, не имеющие точного алгоритмического решения.
Вот и давайте поговорим про нейронные сети, генетические алгоритмы, задачи…
A Gentle Introduction to Hypotheses in Machine Learning
What is a Hypothesis in Machine Learning?
https://machinelearningmastery.com/what-is-a-hypothesis-in-machine-learning/
What is a Hypothesis in Machine Learning?
https://machinelearningmastery.com/what-is-a-hypothesis-in-machine-learning/
MachineLearningMastery.com
What is a Hypothesis in Machine Learning? - MachineLearningMastery.com
Supervised machine learning is often described as the problem of approximating a target function that maps inputs to outputs.
This denoscription is characterized as searching through and evaluating candidate hypothesis from hypothesis spaces.
The discussion…
This denoscription is characterized as searching through and evaluating candidate hypothesis from hypothesis spaces.
The discussion…
Build your own Robust Deep Learning Environment in Minutes
A guide to the less desirable aspects of deep learning environment configurations
https://towardsdatascience.com/build-your-own-robust-deep-learning-environment-in-minutes-354cf140a5a6
A guide to the less desirable aspects of deep learning environment configurations
https://towardsdatascience.com/build-your-own-robust-deep-learning-environment-in-minutes-354cf140a5a6
Medium
Build your own Robust Deep Learning Environment in Minutes
A guide to the less desirable aspects of deep learning environment configurations
Machine-Learning-A-Probabilistic-Perspective.pdf
25.1 MB
Machine Learning A Probabilistic Perspective
Kevin P. Murphy
Kevin P. Murphy
Announcement: TensorFlow 2.0 Has Arrived!
Few months ago I mentioned some of the exciting new features that will be included in TensorFlow 2.0.
https://towardsdatascience.com/announcement-tensorflow-2-0-has-arrived-ee59283fd83a
Few months ago I mentioned some of the exciting new features that will be included in TensorFlow 2.0.
https://towardsdatascience.com/announcement-tensorflow-2-0-has-arrived-ee59283fd83a
Medium
Announcement: TensorFlow 2.0 Has Arrived!
Few months ago I mentioned some of the exciting new features that will be included in TensorFlow 2.0.
Exploring Neural Networks with Activation Atlases
http://ai.googleblog.com/2019/03/exploring-neural-networks.html
http://ai.googleblog.com/2019/03/exploring-neural-networks.html
Googleblog
Exploring Neural Networks with Activation Atlases
How to Demonstrate Your Basic Skills with #DeepLearning
https://machinelearningmastery.com/how-to-demonstrate-basic-deep-learning-competence/
https://machinelearningmastery.com/how-to-demonstrate-basic-deep-learning-competence/
MachineLearningMastery.com
How to Demonstrate Your Basic Skills with Deep Learning - MachineLearningMastery.com
Skills in deep learning are in great demand, although these skills can be challenging to identify and to demonstrate.
Explaining that you are familiar with a technique or type of problem is very different to being able to use it effectively with open source…
Explaining that you are familiar with a technique or type of problem is very different to being able to use it effectively with open source…
Forwarded from Python/ django
How to get started with Python for Deep Learning and Data Science
A step-by-step guide to setting up Python for a complete beginner
https://medium.freecodecamp.org/how-to-get-started-with-python-for-deep-learning-and-data-science-3bed07f91a08
A step-by-step guide to setting up Python for a complete beginner
https://medium.freecodecamp.org/how-to-get-started-with-python-for-deep-learning-and-data-science-3bed07f91a08
freeCodeCamp.org
How to get started with Python for Deep Learning and Data Science
By Joseph Lee Wei En A step-by-step guide to setting up Python for a complete beginner You can code your own Data Science or Deep Learning project in just a couple of lines of code these days. This is not an exaggeration; many programmers out there ...