Tensorflow(@CVision)
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اخبار حوزه یادگیری عمیق و هوش مصنوعی
مقالات و یافته های جدید یادگیری عمیق
بینایی ماشین و پردازش تصویر

TensorFlow, Keras, Deep Learning, Computer Vision

سایت دوره
http://class.vision

👨‍💻👩‍💻پشتیبان دوره ها:
@classvision_support
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Deep Learning 2016: The Year in Review

http://www.deeplearningweekly.com/blog/deep-learning-2016-the-year-in-review

✔️ #Unsupervised and #Reinforcement Learning
✔️ Deep Reinforcement Learning
✔️ #Generative Models
✔️ Continued Openness in AI development
✔️ Partnerships & Acquisitions
✔️ Hardware & Chips

(by Jan Bussieck on December 31, 2016)

In order to understand trends in the field, I find it helpful to think of developments in #deep_learning as being driven by three major frontiers that limit the success of #artificial_intelligence in general and deep learning in particular. Firstly, there is the available #computing power and #infrastructure, such as fast #GPUs, cloud services providers (have you checked out Amazon's new #EC2 P2 instance ?) and tools (#Tensorflow, #Torch, #Keras etc), secondly, there is the amount and quality of the training data and thirdly, the algorithms (#CNN, #LSTM, #SGD) using the training data and running on the hardware. Invariably behind every new development or advancement, lies an expansion of one of these frontiers.
...
Tensorflow(@CVision)
VQABQ: Visual Question Answering by Basic Questions 🔗 https://arxiv.org/abs/1703.06492 #VQA #deep_learning #computer_vision #NLP #Image_captioning #GRU #LSTM #CNN
مرتبط با مقاله: https://t.me/cvision/198

نمونه سوالات:
i. طبقه بندی صحنه: آیا این یک روز بارانی است؟
ii. بازشناسی شیء: چه چیزی بر روی میز است.
iii. طبقه بندی ویژگی: زمین چه رنگی است؟
iv. شمارش: چند نفر در اتاق هستند؟
v. تشخیص شی: آیا سیبی در تصویر وجود دارد؟
vi. تشخیص فعالیت: مرد در حال انجام چه نوع ورزشی است ؟

مقالات مشابه:
https://t.me/cvision/196

#VQA #deep_learning #computer_vision #NLP #Image_captioning
#GRU #LSTM #CNN
#کورس #آموزش
دوره رایگان آموزش مبانی یادگیری عمیق توسط ماکروسافت
این دوره از 5 تیر 96 آغاز شده و طول این دوره 6 هفته است.
در این دوره با فریم ورک CNTK یا Microsoft Cognitive Toolkit آشنا خواهید شد.

Free EDX Course: " Deep Learning Explained "
Starts - Jun 27, 2017
Course Syllabus:
Week 1: Introduction to deep learning and a quick recap of machine learning concepts.
Week 2: Building a simple multi-class #classification model using logistic regression
Week 3: Detecting digits in hand-written digit image, starting by a simple end-to-end model, to a deep neural network
Week 4: Improving the hand-written digit #recognition with #convolutional network
Week 5: Building a model to forecast time data using a #recurrent network
Week 6: Building text data application using recurrent #LSTM (long short term memory) units

🔗 https://www.edx.org/course/deep-learning-explained-microsoft-dat236x

#course #Microsoft #edx #deep_learning #CNTK
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هوش مصنوعی با فرهنگ و ادب 🙂
شعرسرایی شبکه عصبی عمیق به زبان پارسی

#deep_learning #LSTM
صفحه این محقق و پایان نامه ایشون برای علاقه مندان به LSTM و شبکه های Recurrent خصوصا برای بازشناسی جملات دست نویس توصیه میشود.
Alex Graves
https://www.cs.toronto.edu/~graves/

#lstm #handwriting #rnn
#آموزش

Recognizing Speech Commands Using Recurrent Neural Networks with Attention

https://towardsdatascience.com/recognizing-speech-commands-using-recurrent-neural-networks-with-attention-c2b2ba17c837

سورس کد:

A Keras implementation of neural attention model for speech command recognition
https://github.com/douglas125/SpeechCmdRecognition

مرتبط با:

سورس و مقاله wav2letter++ یک روش end2end
https://t.me/cvision/850
جلسه مربوط به Attention در RNNها:
https://www.aparat.com/v/SPZzH
جلسه مربوط به پردازش صوت در RNNها:
https://www.aparat.com/v/cEKal

#attention #rnn #lstm #keras #Speech
#سورس_کد
پیش بینی قیمت بورس با GAN

https://towardsdatascience.com/aifortrading-2edd6fac689d


A complete process for predicting stock price movements. For that purpose a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator are used.

🙏Thanks to: @vahidreza01
#lstm #gan