Adnan Masood, a Machine Learning Phd's musings on Life, Technology, Research & Development
Oh ChatGPT, thy language doth flow so fair,A parrot thou mayst be, yet still so rare.Thy words doth mimic human thought so well,But to true understanding, thou doth not excel. Thy knowledge, though vast, doth have a cut-off date,And biases doth lurk within thy innate.Thy fine-tuning doth bring some customization,But true originality, thou dost lack…
Natural Language Processing Specialization is a comprehensive, hands-on concentration by Deep Learning AI, offered by Coursera. If you have been started working with NLP, and would like to understand the fundamentals and go beyond using libraries (CoreNLP, NLTK, etc), these four courses will provide you a good foundation to help build real-world solutions. Even if…
Last week, I had the opportunity to participate as a mentor in the MIT COVID-19 Datathon working on coronavirus infodemic to identify myths, misinformation, and fake news associated with the pandemic. Out of 2,750 participants and 412 teams, our team qualified to be the top 10 semi-finalists. The MIT COVID-19 Datathon is a week-long virtual…
Last week Microsoft has announced that Apache Spark on Azure HDInsight (Microsoft’s managed Hadoop and Spark cloud service) is now generally available. I spoke to Tampa Bay Data Science Group last night regarding Apache Spark on Azure HDInsight and the associated offerings. Spark for Azure HDInsight offers customers an enterprise-ready Spark solution that’s fully managed, secured, and highly available…
John Foreman in, Data Smart: Using Data Science to Transform Information into Insight works towards a A Workable Definition of Data Science, which is definitely an excellent read. To an extent, data science is synonymous with or related to terms like business analytics, operations research, business intelligence, competitive intelligence, data analysis and modeling, and knowledge extraction (also called knowledge…
The Fallacies of Data Science
1. Correlation = Causation, and Big Data = Information and Insights because Data Context Doesn't Matter.
2. The random nature of the event drives the distribution, therefore the likely distribution also drive the events.
3. Base Rate Fallacy only applies to small data-sets.