Listed below are all my projects, please click and know more on project desc and to view the project...
Breast Cancer Classification
Accuracy: 99.1
Using Decision Tree, Random Forest, Logistic Regression with Dimension reduction
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Breast cancer is one of the most common cancer types among women, and early detection can be a lifesaving health concern. This study aims to explore the potential of an artificial intelligence-based approach in breast cancer diagnosis.
Personal Loan Campaign Purchase Prediction
Using classification techniques(Logistic regression, KNN, Naive Bayes).
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Goal: The classification goal is to predict the likelihood of a liability customer buying personal loans.
Credit Card Users Churn Prediction
Using • Logistic Regression
• Decision Tree Classifier
• Random Tree Classifier
• Bagging Classifier
• Gradient Boosting Classifier
• AdaBoost Classifier
• XGBoost Classifier
• Hyperparameter Tuning
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Developed a classification model aimed at enhancing the bank's services to prevent customers from canceling their credit cards.
Statistical Analysis of Business Data
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Objective: • Statistical Analysis of Business Data. Explore the dataset and extract insights from the data. The idea is for you to get comfortable with doing statistical analysis in Python.
Problems on Probability Travel Package Purchase
Using
• Decision Tree Classifier
• Random Forest Classifier
• Bagging Classifier
• AdaBoost Classifier
• Gradient Boosting Classifier
• XGBoost Classifier
• Stacking Models
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Analyze the data and come up with a predictive model to determine if a customer will leave the credit card services or not and the reason behind it.
Ecommerce product recommendation system
Rank Based Product Recommendation System
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Objective:
• Recommend products with highest number of ratings.
• Target new customers with most popular products.
Ecommerce product recommendation system
Similarity based Collaborative filtering System
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Objective: • Provide personalized and relevant recommendations to users.
Ecommerce product recommendation system
Model based Collaborative filtering System
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Objective: • Provide personalized recommendations to users based on their past behavior and preferences, while also addressing the challenges of sparsity and scalability that can arise in other collaborative filtering techniques.
Signal Processing
Using Neural Network
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Objective: • To build a classifier which can use the given parameters to determine the signal strength or quality.
Movie Reviews Sentiment Classification
Using Sequential NLP classification
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Objective: • To Build a sequential NLP classifier which can use input text parameters to determine the customer sentiments.
Sarcasm Detection - News Headlines
Using Sequential NLP Author Birth Sign Detection From blog authorship corpus
Using Statistical NLP
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Objective: • To build a NLP classifier which can use input text parameters to determine the label/s of the blog. Specific to this case study, you can consider the text of the blog: ‘text’ feature as independent variable and ‘topic’ as dependent variable
Chat Bot
Using Statistical NLP
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Customer support Chat Bot Using Statistical NLP
Plant Seeding Classification
Using Convolution Neural Networks (CNN)
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Objective: • To create a classifier capable of determining a plant's species from a photo.
Flower Image classifier
Using Convolution Neural Networks (CNN) Architecture
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Objective: • To experiment with various approaches to train an image classifier to predict type of flower from the image.
Face Mask Detection
Face Recognition Azure ML SDK and Deploying Model in Azure
Building and Deploying ML model in Azure Azure Computer Vision Service
Demo of Azure Computer Vision Service Bot using Azure Language Services
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Bot using Azure Cognitive Services Language Studio & Python SDK
Azure OpenAI Services
Case study on AI Solution - Paper
