TensorFlow RNN Tutorial
🔗 https://svds.com/tensorflow-rnn-tutorial/
🔗 https://github.com/silicon-valley-data-science/RNN-Tutorial
#TensorFlow #rnn #tutorial
🔗 https://svds.com/tensorflow-rnn-tutorial/
🔗 https://github.com/silicon-valley-data-science/RNN-Tutorial
#TensorFlow #rnn #tutorial
Silicon Valley Data Science
TensorFlow RNN Tutorial - Silicon Valley Data Science
Short tutorial for training a RNN for speech recognition, utilizing TensorFlow, Mozilla's Deep Speech, and other open source technologies
#آموزش
آموزش مقدماتی تنسرفلو برای کسانی که تازه میخواهند شروع کنند...
TensorFlow #Tutorial For Beginners
https://www.datacamp.com/community/tutorials/tensorflow-tutorial#gs.JgGN_V8
—
مطالب مرتبط :
تحلیل با رویکرد کلان داده از کارگروه کلان داده شریف,
جلسه چهارم: مقدمات تنسورفلو
https://t.me/cvision/139
تحلیل با رویکرد کلان داده از کارگروه کلان داده شریف,
جلسه پنجم: پیاده سازی شبکه عصبی کانولوشنالی با تنسرفلو
https://t.me/cvision/162
#TensorFlow
آموزش مقدماتی تنسرفلو برای کسانی که تازه میخواهند شروع کنند...
TensorFlow #Tutorial For Beginners
https://www.datacamp.com/community/tutorials/tensorflow-tutorial#gs.JgGN_V8
—
مطالب مرتبط :
تحلیل با رویکرد کلان داده از کارگروه کلان داده شریف,
جلسه چهارم: مقدمات تنسورفلو
https://t.me/cvision/139
تحلیل با رویکرد کلان داده از کارگروه کلان داده شریف,
جلسه پنجم: پیاده سازی شبکه عصبی کانولوشنالی با تنسرفلو
https://t.me/cvision/162
#TensorFlow
Datacamp
TensorFlow Tutorial For Beginners
In this TensorFlow beginner tutorial, you'll learn how to build a neural network step-by-step and how to train, evaluate and optimize it.
معرفی #کورس، #آموزش
DeepSchool.io
⭕️Contents:
Lesson 0: Introduction to regression.
Lesson 1: Penalising weights to fit better (scikit learn intro)
Mathematics (optional)
Lesson 2: Gradient Descent. Using basic optimisation methods.
Lesson 3: Tensorflow intro: zero layer hidden networks (i.e. normal regression).
Lesson 4: Tensorflow hidden layer introduction.
Deep Learning
Lesson 5: Using #Keras to simplify multi layer neural nets.
Lesson 6: Embeddings to deal with categorical data. (Keras)
Lesson 7: Word2Vec. Embeddings to visualise words. (#Tensorflow)
Lesson 8: Application - Bike Sharing predictions
Lesson 9: Choosing Number of Layers and more
Lesson 10: XGBoost - A quick detour from Deep Learning
Lesson 11: Convolutional Neural Nets (MNIST dataset)
Lesson 12: CNNs and BatchNormalisation (CIFAR10 dataset)
Lesson 13: Transfer Learning (Dogs vs Cats dataset)
Advanced Topics
Lesson 14: LSTMs - Sentiment analysis.
Lesson 15: LSTMs - Shakespeare.
Lesson 16: LSTMs - Trump Tweets.
Lesson 17: Trump - Stacking and Stateful LSTMs.
Lesson 18: Fake News Classifier
🔗Deep Learning tutorials in jupyter notebooks:
http://www.deepschool.io
🔗 YouTube Playlist:
https://www.youtube.com/playlist?list=PLIx9QCwIhuRS1SPS9LHF7VjvZyM1g2Swz
#deep_learning #tutorial
DeepSchool.io
⭕️Contents:
Lesson 0: Introduction to regression.
Lesson 1: Penalising weights to fit better (scikit learn intro)
Mathematics (optional)
Lesson 2: Gradient Descent. Using basic optimisation methods.
Lesson 3: Tensorflow intro: zero layer hidden networks (i.e. normal regression).
Lesson 4: Tensorflow hidden layer introduction.
Deep Learning
Lesson 5: Using #Keras to simplify multi layer neural nets.
Lesson 6: Embeddings to deal with categorical data. (Keras)
Lesson 7: Word2Vec. Embeddings to visualise words. (#Tensorflow)
Lesson 8: Application - Bike Sharing predictions
Lesson 9: Choosing Number of Layers and more
Lesson 10: XGBoost - A quick detour from Deep Learning
Lesson 11: Convolutional Neural Nets (MNIST dataset)
Lesson 12: CNNs and BatchNormalisation (CIFAR10 dataset)
Lesson 13: Transfer Learning (Dogs vs Cats dataset)
Advanced Topics
Lesson 14: LSTMs - Sentiment analysis.
Lesson 15: LSTMs - Shakespeare.
Lesson 16: LSTMs - Trump Tweets.
Lesson 17: Trump - Stacking and Stateful LSTMs.
Lesson 18: Fake News Classifier
🔗Deep Learning tutorials in jupyter notebooks:
http://www.deepschool.io
🔗 YouTube Playlist:
https://www.youtube.com/playlist?list=PLIx9QCwIhuRS1SPS9LHF7VjvZyM1g2Swz
#deep_learning #tutorial