I am a data scientist with experience in utilizing machine learning techniques to extract insights and make predictions from large datasets. My expertise lies in leveraging data to drive business decisions and improve performance. I have a strong background in statistics and programming, and I am always eager to learn new techniques and tools to improve my data analysis skills.
- Programming: Python, R, SQL
- Machine Learning: Supervised and Unsupervised learning, Deep Learning, Natural Language Processing, Computer Vision
- Data Visualization: Matplotlib, Seaborn, Plotly, Tableau
- Statistics: Probability, Inferential Statistics, Bayesian Statistics
- Tools: Jupyter Notebook, Git, and Linux
- CSV with LLM: Slow due to insufficiet hardware support
- Face and liveness detection: Ready to deployable
- Customer Segmentation: Implemented unsupervised learning techniques to segment customers by purchase behavior. Utilized R, k-means clustering, and PCA.
- Mental health prediction:Mental health prediction uses various techniques such as machine learning algorithms, statistical analysis, and natural language processing on a dataset of psychological or behavioral information to identify patterns and predict an individual's mental health status.
- Email: [email protected]
- LinkedIn: Sam-Joshua
- Twitter: SAM_JOSHUA_S
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent