I implemented the modified random forest from scratch in R. Although I tried hard to improve my code and implement some parts in C++ (via Rcpp package), it was still so slow… I noticed random forests packages in R or Python were all calling codes writing in C at its core. So, ...
Implement Text Auto Completion with LSTM This course will teach you how to build a system for email auto-completion from scratch using Python and Keras. You'll learn the internal intricacies of LSTM networks and how they can be used to build systems for the task of text autocompletion. ...
And it might be even better to implement this all from scratch with the PyTorch Extension API to avoid the O(log N) Python loop for extra speed ups. In contrast, if you want to define Child-Sum Tree-LSTMs, the general graph propagation scheme from my previous reply is the way to go...
How to train a semi-supervised GAN from scratch on MNIST and load and use the trained classifier for making predictions. Do you have any questions? Ask your questions in the comments below and I will do my best to answer. Develop Generative Adversarial Networks Today! Develop Your GAN Models...
Learnt about lstms and seq2seq word embeddings to build a chatbot All set for the hackathon tomorrow! Day 96 (15-12-18) Sequence Models Completed Week 1 of Andrew NG's Sequence Models course Working on the Jazz production with lstms problem statement Successfully submitted the Acko Hackathon...
Code a Stacking Ensemble From Scratch in Python, Step-by-Step. Ensemble methods are an excellent way to improve predictive performance on your machine learning problems. Stacked Generalization or stacking is an ensemble technique that uses a new model to learn how to best combine the predictions ...