How to derive sentence-level embedding from word embeddings — The sentence (phrase or passage) level embedding is often used as input in many NLP classification problems, for example, in spam detection and question-answering (QA) systems. In my previous post Discovering Trends in BERT Embeddings of Different Levels for the Task of Semantic Context Determining, I discussed how you might…

How to extract information about the context of a sentence with BERT model outputs — Talking about contextual embeddings in BERT, we mean the hidden states of a pre-trained model. To start with, however, BERT uses non- contextual, pre-trained (static) embeddings being taken from the look-up table. …

Neural networks have been successfully used to tackle a wide range of challenging problems in science and engineering. The example in this article uses Keras to build a neural network that performs multi-output regression for stock and gold price forecasting. …

In recent times, the field of machine learning has largely shifted to neural networks. While a neural network (a deep learning model) typically requires more computational processing power than a regular machine learning model, it often yields more accurate results. A typical neural network requires lots of training — stepping…

SQL is the primary tool for accessing and manipulating data in many databases. It is designed to work with tabular data stored in a database’s containers referred to as tables, allowing you to efficiently access, group, merge and analyze data from different tables. Pandas library, in turn, is designed to…

Being a robust method of data analysis that enables building of applications that can learn from data, machine learning is used in many fields, including predictive analysis, learning associations, anomaly detection, natural language processing (NLP), and image analysis. …

Learn to use word vectors to calculate the semantic similarity of texts programmatically — In a nutshell, word vectors are nothing but the series of real numbers that represent the meanings of natural language words. This technology is an important enabler of useful NLP capabilities that allow machines to “understand” human language. This article discusses how you can use word vectors to programmatically calculate…

If you search for ways to improve your stock investment skills, you’ll definitely find ‘do some research’ among other things. The decision on whether to buy, sell, or hold the stock is often taken based on emotions, which is definitely not the best strategy. To make balanced choices, you need…

It’s quite common nowadays to employ computer technologies to predict stock returns. Thus, many stock prediction algorithms rely on machine learning technology to search patterns and insights in stock data. Before you can do that however, you first need to obtain a data set with necessary stock data and then…