HARIHANTH JULAKANTI

As a recent graduate with an MSc in Data Science and Analytics from the University of Hertfordshire, extensive knowledge has been gained in the areas of Data Science, Machine Learning, and Neural Networks. With aspirations of becoming a Data Analyst, focus is on securing a position in an organization that recognizes the importance of strong interpersonal skills and values team collaboration. An opportunity is being sought to work in an environment that presents challenges to take on high levels of responsibility while continuously developing analytical skills. The aim is to contribute to the organization's success by utilizing data analysis expertise and providing actionable insights that drive effective decision-making.

1) Age and Gender classification techniques using CNN

• Developed an age and gender classification model using the DenseNet technique and TensorFlow and Keras models for image analysis.

2) Financial tweet classification using natural language processing

• Conducted a systematic literature review on the use of natural language processing to extract valuable insights from financial data on Twitter.
• Used Python libraries like NLTK, sci-kit-learn and TensorFlow to develop a model for financial tweet classification.

3) Correlation analysis of cholesterol and maximum heart rate achieved

• Analysed a dataset on cholesterol and maximum heart rate using statistical methods, including the Pearson correlation test, to determine the correlation between the two variables.

4) Sport and business data analysis using the WEKA toolkit

• Applied Term Frequency and Inverse Document Frequency (TF-IDF) transformations on sports and business datasets, and analysed them using three different classifiers: J48, Naïve Bayes, and Decision Tree.

4) Legal and Ethical Framework for misinformation remover

• Conducted a case study on the ethical and legal implications of a misinformation remover plugin and identified relevant ethical and legal issues through a systematic analysis of the scenario.
• Conducted a comprehensive analysis of the General Data Protection Regulation (GDPR) with my team.

5) Wine quality data analysis using mathematical techniques

• Analysed a wine quality dataset using various mathematical techniques, including Principal Component Analysis, Variance, Standard Deviation, and Linear Regression algorithms.

6) Report Writing

• Conducted a detailed review of a data science blog, "A Hands-On Introduction to Hugging Face's AutoNLP 101," and prepared a comprehensive report on linear regression, deep learning, Principal Component Analysis, and software packages like NumPy, SciPy, sci-kit- learn, or Java/Hadoop techniques used in the blog.