Ashu Rani

Extensive 4+ years of experience with Expertise in domain Python, Machine Learning, Deep Learning, AI, NLP, WorkFusion & , Web Crawling, Azure DevOps & Core Java. Passionate about learning new software technologies and able to work independently with little to no supervision as well as functioning as an excellent team player.

• Data Trained Education, Bengaluru, Karnataka 2022-02-16
• PG Program in Data Science, Machine Learning & Neural Network
• IBM 2022-02-16
• Applied Machine Learning with Python
• IT Training Institute, Mumbai 2022-02-15
• Tableau Desktop Professional Certification
• Automation Academy 2021-11-30
• Certification in RPA (WorkFusion
• PROJECT
• Domain: Banking – Micro-Credit Defaulter-Non-Defaulter classification | Dec’ 2020
• Tech Stack: Python, Jupyter Notebook
• Objective: Build a predictive model for detecting defaulter and non-defaulter users
• Solution: Did EDA, treated data imbalance using SMOTE, built multiple models & did hyperparameter tuning for best performing models in each category, treated outliers using percentile approach without removing the data
• Key Achievements: Decision Tree on SMOTE oversampling as a final model with AUC,0.94
• Domain: Social Media – Malignant-Comments-Classifier | Nov’ 2020
• Tech Stack: Python, Jupyter Notebook
• Key Achievements: Decision Tree on SMOTE oversampling as a final model with AUC,0.94
• Domain: Social Media – Malignant-Comments-Classifier | Nov’ 2020
• Tech Stack: Python, Jupyter Notebook
• Objective: Build a predictive model for detecting online hate and abuse comments
• Solution: Did EDA, built multiple models & did hyperparameter tuning for best performing models in each category, treated outliers using percentile approach without removing the data
• Key Achievements: Random Forest Classifier as a final model with Accuracy 95.77%
• Domain: RPA – COKE Florida (CCBF) | Aug 2021
• Tech Stack: Python, Machine Learning, Maven, Work Fusion, Control Tower, Framework
• Objective: Deployed bots using Intelligent Automation studio and run on control tower

• [PG Program in Data Science, Machine Learning & Neural Network], Data Trained Education, Bengaluru, Karnataka - [2021- 2022]
• [Applied Machine Learning with Python], IBM - [2021-2022]
• [Tableau Desktop Professional Certification], IT Training Institute, Mumbai - [Feb 2022]
• Certification in RPA, WorkFusion Automation Academy - [Aug 2021- Dec 2022]
• [Microsoft Power Apps PL-900], Microsoft - [July 2022]
• [Microsoft Azure Fundamental AG -900], Microsoft - [Aug 2022]

Domain: Banking – Micro-Credit Defaulter-Non-Defaulter classification | Dec’ 2020
Tech Stack: Python, Jupyter Notebook
Objective: Build a predictive model for detecting defaulter and non-defaulter users.
Solution: Did EDA, treated data imbalance using SMOTE, built multiple models & did hyperparameter tuning
for best performing models in each category, treated outliers using percentile approach without removing the
data.
Key Achievements: Decision Tree on SMOTE oversampling as a final model with AUC,0.94

Domain: Social Media – Malignant-Comments-Classifier | Nov’ 2020
Tech Stack: Python, Jupyter Notebook
Objective: Build a predictive model for detecting online hate and abuse comments.
Solution: Did EDA, built multiple models & did hyperparameter tuning for best performing models in each
category, treated outliers using percentile approach without removing the data.
Key Achievements: Random Forest Classifier as a final model with Accuracy 95.77%

Domain: RPA – COKE Florida (CCBF) | Aug 2021
Tech Stack: Python, Machine Learning, Maven, Work Fusion, Control Tower, Framework
Objective: Deployed bots using Intelligent Automation studio and run on control tower