3 ways to create a Keras model with TensorFlow 2.0
Link to article and codes
#Tensorflow #Keras
🔭 @DeepGravity
Link to article and codes
#Tensorflow #Keras
🔭 @DeepGravity
#Tensorflow 2.0 coding workshop notebooks
At our meetup Data Science for Internet of Things, Dan Howarth conducted a workshop on tensorflow 2.0
we plan to convert it into another book on data science central. for a set of all previous free books see free datascience books. The notebooks are
tensorflow 2.0: Notebook 1: 'Hello World' Deep Learning with Tensor...
tensorflow 2.0: Notebook 2: Computer Vision with CNNs
tensorflow 2.0: Notebook 3: Transfer Learning
You can see the tensorflow 2.0 roadmap and overall features of tensorflow 2.0. Comments welcome. We hope you like them.
Link to the paper
🔭 @DeepGravity
At our meetup Data Science for Internet of Things, Dan Howarth conducted a workshop on tensorflow 2.0
we plan to convert it into another book on data science central. for a set of all previous free books see free datascience books. The notebooks are
tensorflow 2.0: Notebook 1: 'Hello World' Deep Learning with Tensor...
tensorflow 2.0: Notebook 2: Computer Vision with CNNs
tensorflow 2.0: Notebook 3: Transfer Learning
You can see the tensorflow 2.0 roadmap and overall features of tensorflow 2.0. Comments welcome. We hope you like them.
Link to the paper
🔭 @DeepGravity
Google
Google Colaboratory
This respository contains my exploration of the newly released TensorFlow 2.0. #TensorFlow team introduced a lot of new and useful changes in this release; automatic mixed precision training, flexible custom training, distributed GPU training, enhanced ops for the high-level #Keras API are some of my personal favorites. You can see all of the new changes here.
🔭 @DeepGravity
🔭 @DeepGravity
GitHub
TF-2.0-Hacks/README.md at master · sayakpaul/TF-2.0-Hacks
Contains my explorations of TensorFlow 2.x. Contribute to sayakpaul/TF-2.0-Hacks development by creating an account on GitHub.
@DeepGravity - A very cool intro to Keras and CNN.rar
120.8 MB
Download a very cool intro to #Keras and #CNNs
Syllabus:
Keras 1, What is Keras
Keras 2, Installations for #DeepLearning, #Anaconda, #Jupyter Notebook, #Tensorflow, Keras
Keras 3, #NeuralNetwork Regression Model with Keras
Keras 4, Breast Cancer Diagnosis with Neural Networks
Keras 5, Understanding #ConvolutionalNeuralNetworks, Making a Handwritten Digit Calculator
Watch more videos on the related YouTube channel
🔭 @DeepGravity
Syllabus:
Keras 1, What is Keras
Keras 2, Installations for #DeepLearning, #Anaconda, #Jupyter Notebook, #Tensorflow, Keras
Keras 3, #NeuralNetwork Regression Model with Keras
Keras 4, Breast Cancer Diagnosis with Neural Networks
Keras 5, Understanding #ConvolutionalNeuralNetworks, Making a Handwritten Digit Calculator
Watch more videos on the related YouTube channel
🔭 @DeepGravity
François #Chollet is the creator of #Keras, which is an open source #DeepLearning library that is designed to enable fast, user-friendly experimentation with #deepNeuralNetworks. It serves as an interface to several deep learning libraries, most popular of which is #TensorFlow, and it was integrated into TensorFlow main codebase a while back. Aside from creating an exceptionally useful and popular library, François is also a world-class #AI researcher and software engineer at #Google, and is definitely an outspoken, if not controversial, personality in the AI world, especially in the realm of ideas around the future of #ArtificialIntelligence. This conversation is part of the Artificial Intelligence podcast.
Link
🔭 @DeepGravity
Link
🔭 @DeepGravity
YouTube
François Chollet: Keras, Deep Learning, and the Progress of AI | Lex Fridman Podcast #38
DeepLearning Academy courses
Applied Deep Learning for Predictive Analytics
Deep Learning with #TensorFlow
#DeepLearning
#Course
🔭 @DeepGravity
Applied Deep Learning for Predictive Analytics
Deep Learning with #TensorFlow
#DeepLearning
#Course
🔭 @DeepGravity
Deeplearning-Academy
Courses
Advanced Deep Learning Education and mentoring platform | Learn and practice on real Data Science projects | Get prepared to work as a Deep Learning Engineer.
Semantic Image #Segmentation with #DeepLab in #TensorFlow
Semantic image segmentation, the task of assigning a semantic label, such as “road”, “sky”, “person”, “dog”, to every pixel in an image enables numerous new applications, such as the synthetic shallow depth-of-field effect shipped in the portrait mode of the Pixel 2 and Pixel 2 XL smartphones and mobile real-time video segmentation. Assigning these semantic labels requires pinpointing the outline of objects, and thus imposes much stricter localization accuracy requirements than other visual entity recognition tasks such as image-level classification or bounding box-level detection.
Link
🔭 @DeepGravity
Semantic image segmentation, the task of assigning a semantic label, such as “road”, “sky”, “person”, “dog”, to every pixel in an image enables numerous new applications, such as the synthetic shallow depth-of-field effect shipped in the portrait mode of the Pixel 2 and Pixel 2 XL smartphones and mobile real-time video segmentation. Assigning these semantic labels requires pinpointing the outline of objects, and thus imposes much stricter localization accuracy requirements than other visual entity recognition tasks such as image-level classification or bounding box-level detection.
Link
🔭 @DeepGravity
Datasciencecentral
Semantic Image Segmentation with DeepLab in TensorFlow
This article was written by Liang-Chieh Chen and Yukun Zhu.
Semantic image segmentation, the task of assigning a semantic label, such as “road”, “sky”, “person…
Semantic image segmentation, the task of assigning a semantic label, such as “road”, “sky”, “person…
#TensorFlow 2 Tutorial: Get Started in #DeepLearning With tf.keras
After completing this tutorial, you will know:
The difference between Keras and tf.keras and how to install and confirm TensorFlow is working.
The 5-step life-cycle of tf.keras models and how to use the sequential and functional APIs.
How to develop MLP, CNN, and RNN models with tf.keras for regression, classification, and time series forecasting.
How to use the advanced features of the tf.keras API to inspect and diagnose your model.
How to improve the performance of your tf.keras model by reducing overfitting and accelerating training.
#Keras
Link
🔭 @DeepGravity
After completing this tutorial, you will know:
The difference between Keras and tf.keras and how to install and confirm TensorFlow is working.
The 5-step life-cycle of tf.keras models and how to use the sequential and functional APIs.
How to develop MLP, CNN, and RNN models with tf.keras for regression, classification, and time series forecasting.
How to use the advanced features of the tf.keras API to inspect and diagnose your model.
How to improve the performance of your tf.keras model by reducing overfitting and accelerating training.
#Keras
Link
🔭 @DeepGravity
MachineLearningMastery.com
TensorFlow 2 Tutorial: Get Started in Deep Learning with tf.keras - MachineLearningMastery.com
Predictive modeling with deep learning is a skill that modern developers need to know. TensorFlow is the premier open-source deep learning framework developed and maintained by Google. Although using TensorFlow directly can be challenging, the modern tf.keras…
Image Data Augmentation for #TensorFlow 2, #Keras and #PyTorch with Albumentations in #Python
TL;DR Learn how to create new examples for your dataset using image augmentation techniques. Load a scanned document image and apply various augmentations. Create an augmented dataset for Object Detection.
Article
🔭 @DeepGravity
TL;DR Learn how to create new examples for your dataset using image augmentation techniques. Load a scanned document image and apply various augmentations. Create an augmented dataset for Object Detection.
Article
🔭 @DeepGravity
Curiousily
Image Data Augmentation for TensorFlow 2, Keras and PyTorch with Albumentations in Python - Adventures in Artificial Intelligence…
Learn how to augment image data for Image Classification, Object Detection, and Image Segmentation
Automating Pac-man with #DeepQLearning: An Implementation in #Tensorflow.
Link
#DeepReinforcementLearning
🔭 @DeepGravity
Link
#DeepReinforcementLearning
🔭 @DeepGravity
Medium
Automating Pac-man with Deep Q-learning: An Implementation in Tensorflow.
Fundamentals of Reinforcement Learning