During the week 1 and week 2, I focused on the Assessment 1 Project Brief on Discussion Board and Blog Setup. As the first step I selected a topic from the list given By Ken.  I was interested in Big Data Analytics in Health Care, AI and Machine Learning in Detecting Fake Information topics. While investigating those topics in Google scholar articles, I found an interesting paper related to Mental health and Machine Learning. As I am passionate about data analytics and AI, I searched articles related to Mental Health and Machine learning. I used “Mental Health”, “Mental disorder identification”, “Machine Learning”, “text analysis”, “Natural Language Processing” key words to find research papers in Google scholar.

Since I have work experience in both Software development and Data analytics, I wanted to select a topic where I can apply both Software development and Data analytics skills. So, I selected “A dashboard to predict mental health disorders using NLP and Machine Learning by analysing social media texts.” as my topic for the project. This project aims to develop a dashboard using R language, Natural Language Processing (NLP) and Machine Learning (ML) techniques to analyse social media texts to predict mental health conditions. Mainly, people can identify the mental disorder by entering social media text using the proposed dashboard.

After selecting the topic I worked on Abstract, Background/Description, Project Aim/Objectives, Project Problem Domain, Deliverables/Outcomes. Latest related research papers were picked according to the guideline given by the university.

I searched for a suitable dataset for this analysis which I can use to train for the ML model. Since I am going to do a supervised learning, I found a suitable dataset from Kaggle.com. The dataset is a collection of labeled mental health statuses from different statements. The dataset is a comprehensive resource for creating chatbots and sentiment analysis; it combines raw data from many sources like reddit, Facebook, twitter social media posts and comments. That dataset has 7 Mental health conditions such as Anxiety, Bipolar, Depression, Personality disorder, Stress, Suicidal and Normal.

Next, I plan to focus on Assessment 2 and further investigation on research papers to address following research questions.

• How NLP can be used for this prediction and analysis of text?
• What is the most suited classification method to classify text and documents in machine learning specially in supervised learning?
• What are the advantages of machine learning over traditional methods?