1. AI in HR: Leveraging Machine Learning for Talent Management

• Event: HR Tech Conference, 2022

• Summary: This presentation discusses the integration of AI and machine learning in human resources to optimize talent management. It covers predictive models for employee turnover, recruitment efficiency, and performance forecasting.

• Key Points:

• Predictive analytics for employee turnover.

• Machine learning models for recruitment optimization.

• Case studies demonstrating improved HR outcomes using AI.

• Link: View Presentation on Slideshare

2. Deep Learning Models for Predictive Maintenance

• Event: NeurIPS 2021

• Summary: Focuses on using deep learning techniques to develop predictive maintenance models for industrial equipment. This presentation includes data collection, preprocessing, and model deployment to predict equipment failures.

• Key Points:

• Introduction to predictive maintenance.

• Deep learning techniques and architectures used.

• Real-world applications and success stories.

• Link: Read More on Slideshare

3. Enhancing Customer Experience with AI-Powered Chatbots

• Event: AI Summit, 2020

• Summary: This presentation explores the development and deployment of AI-powered chatbots to enhance customer service. It covers natural language processing, user interaction design, and integration with customer service platforms.

• Key Points:

• Fundamentals of AI chatbots.

• NLP techniques for improving chatbot interactions.

• Case studies of successful chatbot implementations.

• Link: View Presentation on Slideshare

4. Real-Time Data Analytics with Apache Kafka and Spark

• Event: Data Science Conference, 2021

• Summary: Discusses the architecture and implementation of real-time data analytics platforms using Apache Kafka and Spark. It includes case studies on real-time data processing and insights generation.

• Key Points:

• Overview of Apache Kafka and Spark.

• Building scalable real-time data pipelines.

• Use cases and performance optimization strategies.

• Link: View Presentation on Slideshare

5. Advanced Machine Learning Techniques for Financial Forecasting

• Event: Financial Analytics Summit, 2021

• Summary: This presentation covers advanced machine learning techniques for financial forecasting, including time series analysis, regression models, and deep learning. It provides examples from real-world financial datasets.

• Key Points:

• Introduction to financial forecasting with machine learning.

• Time series analysis and regression models.

• Applying deep learning to financial data.

• Link: View Presentation on Slideshare