Aug 2022 – Dec 2024 · 2 yrs 4 mos · India · Remote

• Understanding the Business aspects of Data Science and make data driven decisions.
• Undergoing a 14-month long intensive hands-on Data Science Training with a special focus on the underlying Mathematical concepts.
• Tools
• Python
• SQL
• Excel
• Tableau
• Probability/Statistical Testing
• Probability Distributions
• p-value
• t-test/z-test
• ANOVA
• chi2 test
• Parametric/Non-Parametric Tests
• Correlation Testing
• Product Analytics
• Metrics
• KPI
• Root Cause Analysis
• Customer Segmentation (RFM analytics)
• A/B Testing
• Guess Estimates
• Pattern Recognition 1
• Maximum Likelihood Estimation
• Decision Theory, Information Theory
• Linear Regression OLS
• Logistic Regression, K-NN
• Decision Trees
• Ensemble Learning (Random Forests, GBDT)
• XGBoost
• SVM/SVC
• Pattern Recognition 2
• KMeans/KMeans++
• DBSCAN
• Density Estimation (GMM)
• Hierarchical Clustering
• Outlier/Anomaly/Novelty Detection (LOF, 1 class SVM, Isolation Forests)
• High Dim. Data Viz (PCA, t-SNE, UMAP)
• Computer Vision
• Image Classification (Vision Transformers, Dense Nets, ResNets)
• Image Segmentation (UNET, Attention UNET, UNET++, Residual UNET)
• Object Detection (YOLO, Mask-RCNN, ViT Object Detection)
• Image Augmentation (Albumentations, CutMix)
• Image Enhancement (MIRNet, Sub-pixel CNN, SID, Conv. AE)
• GANs (DCGAN, CycleGAN, StyleGAN)
• Natural Language Processing
• Text Preprocessing
• Word Embeddings (Word2Vec, GloVE, FastText)
• Text Classification
• Language Modelling, Topic Modelling, NER
• 1D Conv, RNN, GRU, bi-GRU, LSTMs
• Attention, Transformers
• BERT, GPT
• MLOps & ML System Design
• Git, GitHub
• Streamlit
• Flask APIs
• Docker
• AWS ECS
• Github Actions (CI/CD Pipelines)
• Experiment Tracking (MLFlow, WanDB)
• ML System Design

Jun 2020 – Jun 2020 · 0 mo · Singapore

• Claritas HealthTech is a healthcare software company based in Singapore, focusing on Image Enhancement (IE), Machine Vision (MV), and Artificial Intelligence (AI). I worked as an intern to develop the following:
• 1) Developed a model which can identify whether a person has Pneumonia or not by analyzing their X-Ray reports (>94% accuracy on the Mendeley Chest X-Ray data set).
• 2) Developed a Diabetic Retinopathy Detection model (>98% accuracy on the APTOS data set).

May 2020 – Aug 2020 · 3 mos · India · Remote

• Crowd sourced natural disaster aftermath images and created a multi label data set and developed a model which can precisely generate a damage report based on the type of location and the severity of the destruction.

May 2020 – Aug 2020 · 3 mos · India

• Worked on a team and developed a light-weight model capable of facilitating communication between a differently abled and a regular person.