Sentiment Analysis Using TensorFlow

AI-Driven Financial Insights: Sentiment Analysis Using TensorFlow

• Created byDiogo Alves de Resende

Lab scenario

As a data scientist at FinInsight Solutions, a trailblazer in financial technology, you are tasked with a pivotal project that could redefine investment strategies. Your expertise is sought by the Product Analytics team to harness the power of sentiment analysis for gauging market trends. Equipped with cutting-edge TensorFlow tools, you will analyze vast streams of financial news and social media to extract actionable insights, deciphering the underlying sentiment that sways investor decisions. The outcome? A sophisticated sentiment analysis model, fine-tuned to forecast market dynamics, which could become an integral component of the company's analytics suite. The CTO has highlighted this project in the quarterly goals, emphasizing its importance in keeping FinInsight Solutions at the forefront of FinTech innovation. Your mission is to deliver a robust model that not only performs with precision but also integrates seamlessly into the existing workflow, serving as a beacon for data-driven investment strategies.

Objectives

• Evaluate sentence length variations within text data using histograms to understand data complexity
• Examine word frequency using the Counter tool and Seaborn visualizations to identify common language patterns
• Identify and visualize the most common bi-grams in a text corpus using NLP feature extraction techniques
• Assess the presence of positive and negative sentiment words within the text data by implementing basic sentiment analysis
• Apply text preprocessing techniques such as tokenization, cleaning, and TF-IDF vectorization to prepare data for machine learning
• Construct a baseline neural network using TensorFlow/Keras to classify text data and interpret model performance metrics
• Optimize a neural network architecture and hyperparameters using Keras Tuner to improve model accuracy
• Build and save a final tuned neural network model, incorporating best practices in model selection and persistence

Skills

• NLP (Natural Language Processing)
• TensorFlow
• Keras
• Neural Networks
• Hyperparameter Tuning
• Text Preprocessing

To do

Utilize TensorFlow to build and train a sentiment analysis model. The data and its documentation are already compiled in the directory, and you should use the Python environment that's been set up on our server. Remember, this model has to be integration-ready, so please make sure it adheres to our code standards and is thoroughly documented.