Machine learning focuses on algorithms and mathematical models that enable computers to do things they are not explicitly designed to do.
Machine learning requires the development of models that can recognize patterns and relationships from data. This model uses acquired knowledge to make informal predictions or decisions for a given task.
For machine learning models to understand how to perform various actions, training datasets must first be fed into the machine learning algorithm, followed by validation datasets (or testing datasets) to ensure that the model is interpreting this data accurately.
Once we feed these training and validation sets into the system, subsequent datasets can then be used to sculpt your machine learning model going forward. The more data you provide to the ML system, the faster that model can learn and improve.
| Sr. No | Project Name | Type | Link |
|---|---|---|---|
| 1. | Air Quality | Regression | Link |
| 2. | Monthly International Airline Passengers | Forecasting | Link |
| 3. | Air Quality in India | EDA | Link |
| 4. | Airline Passenger Satisfaction | Classification | Link |
| 5. | Bike Sharing Demand Analysis | Linear Analysis | Link |