Data Collection by EPIC Translations: Copywriting, Text & Audio Data Data for AI & ML Training

Our expertise ranges from: a) Machine Learning Pipeline, that is, from Data Collection, Data Preprocessing, selection of algorithm that is well suited to deliver the best results based on the challenge, tuning and tweaking of hyperparameters, creation of a multialgorithm pipeline for comparison of different algorithms and how they perform, and finally the delivery of the algorithm to a real-world scenario by creating APIs that can manipulate and translate data to a given output. b) The creation of machine learning packed Microservices that can be used in real-world deployment of the already trained algorithms. c) Web Scrapping. d) Machine Learning Consultation- Based on our knowledge of the machine learning infrastructure we can offer a great deal of expertise on the subject matter. e) Sentiment Analysis - Natural Language Processing (NLP) being one of the disciplines of machine learning gives us a great opportunity to apply sentiment analysis especially in the understanding of text and its context. We have worked on various machine learning projects: a) Using Sentiment Analysis in the categorization of twitter data that we collected from tweepy (Twitter API) into either hate speech that could lead to political instability in a developing country or a neutral sentiment. b) The collection of data, labelling of data, development of machine learning algorithm that was used as a recommender system to advise potential tenants on places that they could rent out depending on a few preferences that they gave and its deployment using an API. c) The development of Reinforcement Learning algorithm that could predict the oil pressure rates based on various factors for use in oil production purposes. d) The collection of audio data, its synthesis, training and deployment into a personal “SIRI” or “CORTANA”. e) A machine learning project to demonstrate and predict the COVID-19 outbreak. f) A machine Learning project based on various crop diseases that was used to categorize crop diseases based on images and their cross relationship with the training data.