General Machine Learning and Artificial Intelligence
You’ll likely be asked questions about data-based modeling, training/testing procedures, error checking, and statistics. For instance, you’ll be asked, “What is a problem definition for machine learning?” You’ll then be asked to define the problem as a machine learning problem and then come up with a solution. You’ll want to think about data sources, annotations, modeling techniques, and pitfalls. It’s also worth revisiting your favorite ML/AI textbooks to ensure you’re familiar with the basics of AI/ML techniques and algorithms.
Some Machine Learning Topics are mentioned below:
Topic |
Link |
---|---|
1. What is Machine Learning? | Link |
2. What are some real-life applications of clustering algorithms? | Link |
3. How to choose an optimal number of clusters? | Link |
4. What is a Hypothesis in Machine Learning? | Link |
5. How do measure the effectiveness of the clusters? | Link |
6. Why do we take smaller values of the learning rate? | Link |
7. What is Overfitting in Machine Learning and how can it be avoided? | Link |
8. Why we cannot use linear regression for a classification task? | Link |
9. Why do we perform normalization? | Link |
10. What are some of the hyperparameters of the random forest regressor which help to avoid overfitting? | Link |
Top Software Development Topics to prepare for Interview
Software development refers to a set of computer science activities dedicated to the process of creating, designing, deploying, and supporting software.
Table of Content
- Programming language
- Data structures
- Algorithms
- System Design
- Coding
- Object-oriented design
- Databases
- Distributed computing
- Operating systems
- Internet topics
- General machine learning and artificial intelligence
- Conclusion