Lstm

LSTM networks are the maestros of deep learning, they compose beautiful music without ever picking up an instrument. They can compose a symphony, but it could be so good that it might have to be encored — recurrently. LSTM (Long Short-Term Memory) neural networks are a powerful tool for processing…

Evidence suggests that the processes producing inflation change over time. The data relevant to determine the inflation rate during recessions may be insignificant during growth periods. That is, the model might change with Business Cycles. It is not straightforward to identify at which point of a cycle the economy is…

Build and deploy your own sentiment classification app using Python and Streamlit — Nowadays, working on tabular data is not the only thing in Machine Learning (ML). Data formats like image, video, text, etc., are getting famous with use cases like image classification, object detection, chat-bots, text generation, and more. One such popular use case is sentiment analysis, the process of determining whether…

Goal — build a system able to make predictions about the physical world and play around with a simulator. Problem + Setup Use open AI gym to simulate physics, collect data and train a models to predict the time for the episode to terminate at a given time step. Open AI inverted pendulum documentation What we did: Created dataset by simulating 10k episodes of the inverted pendulum by taking random actions

The Gated Recurrent Unit is a more striking variant of the LSTM. It creates a single “update gate” by fusing the forget and input gates. To solve the vanishing gradient problem of a standard RNN, GRU uses, the so-called, update gate and reset gate. Basically, these are two vectors that…

Abstract: One of the most thoroughly studied fields of research that is permeating every aspect of our daily life is deep learning. In a nutshell, it is the use of advanced, powerful hardware to implement artificial neural networks. …

I covered time series analysis, changepoint detection, and momentum strategy in my previous three posts. We will discuss how to use all of this knowledge for actual quantitative investing in this post. Previous recap With the hope that the recent performance will continue, traders who use the momentum trading technique try to…

Machine Learning has come across to that level where it can understand natural languages. Today we are going to understand how RNN and LSTM work by creating a sentiment analysis model by the techniques of Natural Language Processing. We will start from the very beginning like what is NLP? and…

In my previous article on Recurrent Neural Networks (RNNs), I discussed RNNs and how they work. Towards the end of the article, the limitations of RNNs were discussed. To refresh our memory, let's quickly touch upon the main limitation of RNNs and understand the need for modifications of vanilla RNNs. …