Sentiment Mining in Finance

oleh Everlytics Data Science
Sentiment Mining in Finance
Sentiment Mining in Finance

This is for a Fintech client that wanted to build a Market Sentiment Visualisation and Trading Dashboard that provides a sentiment-based market outlook for all major financial products. The engagement involved: 1. Design and build of a data pipeline and storage layer: Spark Streaming app that constantly reads the tweets and stores them in MongoDB 2. Algorithm to classify each tweet and assign a sentiment score (PySpark and Spark ML lib) 3. Visualization layer (in Tableau initially and moved to Highcharts later on) About the SentiFin dashboard screenshots that you see: 1. Buy Sell signals based on Sentiment score 2. Top Tweets with -ve and +ve Sentiments As usual, we enjoyed working on this!

image of username Everlytics Data Science Flag of India BANGALORE, India

Tentang Saya

I have 18 yoe in ML, Big Data, BI and related data science works. Focused on helping a few niche technology companies in bringing their (mostly disruptive) ideas to life. A design thinker, responsive and collaborative individual with strong background in data science. My clients engage me to architect and develop solutions that have Big Data and/or Machine Learning as differentiating components. - Predictive Analytics & ML - Big Data Backends - Streaming Data Pipelines - Good Old ETL & BI Machine Learning: Regression, Association (apriori), Classification (decision trees, random forest, logit), Clustering (k-means) Python, Scikit-learn Dataiku, RapidMiner, Azure ML Studio, SageMaker Data Visualisation: Power BI, Tableau, Qlik, Klipfolio, Kibana DW and ETL: Snowflake, BigQuery, Athena, AirFlow, SSIS Stream Processing: Spark, Flume, Kafka, Kafka Streams, Kinesis Elasticsearch (ELK) I believe in simple and future-proof design. Putting trust and satisfaction before money.

$50 USD/jam

16 Ulasan
7.2

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