Natural Language Processing for Stocks News Analysis

4.5
estrelas
11 classificações
oferecido por
Coursera Project Network
Neste projeto guiado, você irá:

Create a pipeline to remove stop-words, perform tokenization and padding

Understand the theory and intuition behind Recurrent Neural Networks and LSTM

Train the deep learning model and assess its performance

Clock2 hours
BeginnerBásico
CloudSem necessidade de download
VideoVídeo em tela dividida
Comment DotsInglês
LaptopApenas em desktop

In this hands-on project, we will train a Long Short Term Memory (LSTM) deep learning model to perform stocks sentiment analysis. Natural language processing (NLP) works by converting words (text) into numbers, these numbers are then used to train an AI/ML model to make predictions. In this project, we will build a machine learning model to analyze thousands of Twitter tweets to predict people’s sentiment towards a particular company or stock. The algorithm could be used automatically understand the sentiment from public tweets, which could be used as a factor while making buy/sell decision of securities. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Habilidades que você desenvolverá

  • Python Programming
  • Machine Learning
  • Deep Learning
  • coding

Aprender passo a passo

Em um vídeo reproduzido em uma tela dividida com a área de trabalho, seu instrutor o orientará sobre esses passos:

  1. Task #1: Understand the Problem Statement and business case 

  2. Task #2: Import libraries and datasets and Perform Exploratory Data Analysis

  3. Task #3: Perform Data Cleaning (Remove Punctuations)

  4. Task #4: Perform Data Cleaning (Remove Stopwords)

  5. Task #5: Plot WordCloud

  6. Task #6: Visualize Cleaned Datasets

  7. Task #7: Prepare the data by tokenizing and padding

  8. Task #8: Understand the theory and intuition behind LSTM

  9. Task #9: Build and train the model

  10. Task #10: Assess trained model performance

Como funcionam os projetos guiados

Sua área de trabalho é um espaço em nuvem, acessado diretamente do navegador, sem necessidade de nenhum download

Em um vídeo de tela dividida, seu instrutor te orientará passo a passo

Avaliações

Principais avaliações do NATURAL LANGUAGE PROCESSING FOR STOCKS NEWS ANALYSIS

Visualizar todas as avaliações

Perguntas Frequentes – FAQ

Perguntas Frequentes – FAQ

Mais dúvidas? Visite o Central de Ajuda ao estudante.