Deep Learning Neural Networks Play Path of Exile
https://www.youtube.com/watch?v=UrrZOswJaow&feature=youtu.be
https://www.youtube.com/watch?v=UrrZOswJaow&feature=youtu.be
YouTube
Deep Learning Neural Networks Play Path of Exile
Four deep learning neural networks work together simultaneously to play the game Path of Exile only using visual input from the game. Project summary video w...
Application of Hierarchical Clustering to 300+ Cryptocurrencies (btc,eth,...) (historical prices)
https://gmarti.gitlab.io/cryptocurrency/2017/08/25/download-cryptocoins-api-python.html
https://gmarti.gitlab.io/cryptocurrency/2017/08/25/download-cryptocoins-api-python.html
gmarti.gitlab.io
Download & Play with Cryptocurrencies Historical Data in Python
To access the CryptoCompare public API in Python, we can use the following Python wrapper available on GitHub: cryCompare.
Fashion-MNIST a MNIST-like fashion product dataset under MIT
https://github.com/zalandoresearch/fashion-mnist
https://github.com/zalandoresearch/fashion-mnist
GitHub
GitHub - zalandoresearch/fashion-mnist: A MNIST-like fashion product database. Benchmark
A MNIST-like fashion product database. Benchmark :point_down: - GitHub - zalandoresearch/fashion-mnist: A MNIST-like fashion product database. Benchmark
Docker Compose + GPU + TensorFlow = ❤️
https://hackernoon.com/docker-compose-gpu-tensorflow-%EF%B8%8F-a0e2011d36
https://hackernoon.com/docker-compose-gpu-tensorflow-%EF%B8%8F-a0e2011d36
Hackernoon
Docker Compose + GPU + TensorFlow = ❤️
Docker is awesome — more and more people are leveraging it for development and distribution. Instant environment setup, platform independent apps, ready-to-go solutions, better version control, simplified maintenance: Docker has a lot of benefits.
Understanding Attentive Recurrent Comparators + a PyTorch implementation
https://medium.com/@sanyamagarwal/understanding-attentive-recurrent-comparators-ea1b741da5c3
https://medium.com/@sanyamagarwal/understanding-attentive-recurrent-comparators-ea1b741da5c3
Medium
Understanding Attentive Recurrent Comparators
I recently came across an ICML’17 paper “Attentive Recurrent Comparators” which proposes a simple yet powerful model for data efficient…
How to Train a Simple Audio Recognition Network
https://www.tensorflow.org/versions/master/tutorials/audio_recognition
https://www.tensorflow.org/versions/master/tutorials/audio_recognition
Automatically Fitting the Support Vector Machine Cost Parameter
https://www.displayr.com/automatically-fitting-the-support-vector-machine-cost-parameter/
https://www.displayr.com/automatically-fitting-the-support-vector-machine-cost-parameter/
Displayr
Automatically Fitting the Support Vector Machine Cost Parameter
I show how to automatically fit the Support Vector Machine cost parameter by automating the manual search for the optimal cost.
[DeepBayes] День 1, лекция 1. Евгений Соколов. Обзор нейросетевых архитектур
https://www.youtube.com/watch?v=R5YUywRz45E&list=PLEqoHzpnmTfBSyGmE4nBlhxxi28dCZwWN&index=2
https://www.youtube.com/watch?v=R5YUywRz45E&list=PLEqoHzpnmTfBSyGmE4nBlhxxi28dCZwWN&index=2
YouTube
[DeepBayes] День 1, лекция 1. Евгений Соколов. Обзор нейросетевых архитектур
[DeepBayes] День 1, лекция 2. Дмитрий Ветров. Введение в байесовские методы
https://www.youtube.com/watch?v=gdlEfmrCklw&list=PLEqoHzpnmTfBSyGmE4nBlhxxi28dCZwWN&index=3
https://www.youtube.com/watch?v=gdlEfmrCklw&list=PLEqoHzpnmTfBSyGmE4nBlhxxi28dCZwWN&index=3
YouTube
[DeepBayes] День 1, лекция 2. Введение в байесовские методы (Дмитрий Ветров)
На школе мы объясним, как байесовские методы и глубинное обучение объединяются в единый формализм, покажем примеры успешного применения нейробайесовских моделей, расскажем про современные методы стохастической оптимизации и основные библиотеки глубинного…
[DeepBayes] День 1, лекция 3. Дмитрий Кропотов. Введение в стохастическую оптимизацию
https://www.youtube.com/watch?v=djh4hBxTZRA&index=4&list=PLEqoHzpnmTfBSyGmE4nBlhxxi28dCZwWN
https://www.youtube.com/watch?v=djh4hBxTZRA&index=4&list=PLEqoHzpnmTfBSyGmE4nBlhxxi28dCZwWN
YouTube
[DeepBayes] День 1, лекция 3. Дмитрий Кропотов. Введение в стохастическую оптимизацию
[DeepBayes] День 1. Дмитрий Кропотов / Кирилл Струминский. Семинар по байесовским методам
https://www.youtube.com/watch?v=qMwkoXi8-dk&index=5&list=PLEqoHzpnmTfBSyGmE4nBlhxxi28dCZwWN
https://www.youtube.com/watch?v=qMwkoXi8-dk&index=5&list=PLEqoHzpnmTfBSyGmE4nBlhxxi28dCZwWN
YouTube
[DeepBayes] День 1. Дмитрий Кропотов / Кирилл Струминский. Семинар по байесовским методам
Space shooter game using TensorFlow to train enemy AI in Python+Go
https://github.com/ActiveState/neuroblast
https://github.com/ActiveState/neuroblast
GitHub
ActiveState/neuroblast
NeuroBlast is a classic arcade space shooter with ML-powered AI. - ActiveState/neuroblast
Multiple Perceptual Tasks With a Single Deep Neural Network
https://www.youtube.com/watch?v=-5wAlxdxuQo
https://www.youtube.com/watch?v=-5wAlxdxuQo
YouTube
"Multiple Perceptual Tasks With a Single Deep Neural Network," a Presentation from Magic Leap
Andrew Rabinovich, Director of Deep Learning at Magic Leap, presents the "Performing Multiple Perceptual Tasks With a Single Deep Neural Network" tutorial at...
Benchmarking Recurrent Networks for Language Modeling
https://danijar.com/benchmarking-recurrent-networks-for-language-modeling
https://danijar.com/benchmarking-recurrent-networks-for-language-modeling
Danijar
Benchmarking Recurrent Networks for Language Modeling
There are many design decisions to make when using recurrent neural networkssuch as LSTM or GRU. I conducted some experiments to see what works well on theTe...
Tensorflow GAN model collection: GAN, LSGAN, WGAN, DRAGAN, CGAN, infoGAN, ACGAN, EBGAN, BEGAN
https://github.com/hwalsuklee/tensorflow-generative-model-collections
https://github.com/hwalsuklee/tensorflow-generative-model-collections
GitHub
GitHub - hwalsuklee/tensorflow-generative-model-collections: Collection of generative models in Tensorflow
Collection of generative models in Tensorflow. Contribute to hwalsuklee/tensorflow-generative-model-collections development by creating an account on GitHub.
How to Reshape Input Data for Long Short-Term Memory Networks in Keras
https://machinelearningmastery.com/reshape-input-data-long-short-term-memory-networks-keras/
https://machinelearningmastery.com/reshape-input-data-long-short-term-memory-networks-keras/
How to Make Predictions with Long Short-Term Memory Models in Keras
https://machinelearningmastery.com/make-predictions-long-short-term-memory-models-keras/
https://machinelearningmastery.com/make-predictions-long-short-term-memory-models-keras/
MachineLearningMastery.com
How to Make Predictions with Long Short-Term Memory Models in Keras - MachineLearningMastery.com
The goal of developing an LSTM model is a final model that you can use on your sequence prediction problem.
In this post, you will discover how to finalize your model and use it to make predictions on new data.
After completing this post, you will know:…
In this post, you will discover how to finalize your model and use it to make predictions on new data.
After completing this post, you will know:…
Python Data Science Handbook
https://jakevdp.github.io/PythonDataScienceHandbook/
https://jakevdp.github.io/PythonDataScienceHandbook/
SVM: Why not to apply an RBF kernel to text classification tasks
https://calculatedcontent.com/2012/02/06/kernels_part_1/
https://calculatedcontent.com/2012/02/06/kernels_part_1/
calculated | content
Kernels Part 1: What is an RBF Kernel? Really?
My first blog on machine learning is to discuss a pet peeve I have about working in the industry, namely why not to apply an RBF kernel to text classification tasks. I wrote this as a follow up to …