mikhail-naumov Goto Github PK
Name: Mikhail Naumov
Type: User
Name: Mikhail Naumov
Type: User
1. Using facebook's Prophet to predict Bitcoin values. 2. Using Reddit comments and scores to measure time series sentiment, as a supplementary feature in a multivariate LSTM RNN.
GridSearching Templates
TensorFlow - A curated list of dedicated resources http://tensorflow.org
Explanation & Exploration for variable Bayesian Optimization vs Grid Search vs Random Search, for hyper parameter optimization.
Projects include the application of transfer learning to build a convolutional neural network (CNN) that identifies the artist of a painting, the building of predictive models for Bitcoin price data using Long Short-Term Memory recurrent neural networks (LSTMs) and a tutorial explaining how to build two types of neural network using as input the MNIST dataset, namely, a CNN using Keras and a fully-connected network using TensorFlow.
Developed a model that can estimate likelihood of success, for an application to the non-profit organization DonorsChoose. Using a LGBM on submission tf-idf essays features, classroom and state demographic.
A Jupyter notebook that uses the Watson Visual Recognition, Natural Language Understanding and Tone Analyzer services to enrich Facebook Analytics and uses PixieDust to explore and visualize the results in Watson Studio
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