Coder Social home page Coder Social logo

Mohd Fitri Alif Bin Mohd Kasai's Projects

kaggle-toxic-comments icon kaggle-toxic-comments

Ensemble stacking using Keras / Tensorflow. Used LSTM RNN, Logistic Regression & XGB Classifier for first level, and simple CNN for metalearning.

kaggle-vote icon kaggle-vote

Tensorflow/Keras implementation of ensemble models for Kaggle Challenge (Voting Prediction)

kaggle_digit_recognizer_with_deap icon kaggle_digit_recognizer_with_deap

Kaggle digit recognizer with deap is an implementation of genetic algorithm that tries to optimize model produced by lenet5 using this CNN option (learning rate, batch size, receptive field etc) as hyperparameters optimized by genetic algo

kaggle_state_farm icon kaggle_state_farm

VGG & Resnet Neural Networks for Kaggle's State Farm Distracted Driver Detection contest (Tensorflow)

kentautoml icon kentautoml

Implementation of a CoDeepNEAT-style AutoML algorithm for developing neural net architectures

keras icon keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.

keras-1 icon keras-1

Good example of Keras ANN, CNN, RNN including merge capabilities and LSTM

keras-android icon keras-android

Implementation of Handwritten digits classification from MNIST on Android using Keras and TensorFlow.

keras-application-zoo icon keras-application-zoo

Reference implementations, Keras code and weights files, of popular deep learning models missing from keras-applications and keras-contrib

keras-bda icon keras-bda

A Bayesian Data Augmentation Approach for Learning Deep Models in Keras

keras-cats-dogs-tutorial icon keras-cats-dogs-tutorial

A practical example of image classifier with Keras 2.x and TensorFlow backend, using the Kaggle Cats vs. Dogs dataset. By taking advantage of Keras' image data augmentation capabilities (and also random cropping), we were able to achieve 99% accuracy on the trained model with only 2,000 images in the training set.

keras-center-loss-mnist icon keras-center-loss-mnist

keras implementation of A Discriminative Feature Learning Approach for Deep Face Recognition based on MNIST

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.