| Define Precision and Recall? |
| What are Different Types of Machine Learning algorithms? |
| What is Supervised Learning? |
| What is Unsupervised Learning? |
| What is ‘Naive’ in a Naive Bayes? |
| What is PCA? When do you use it? |
| What are Support Vectors in SVM? |
| What are Different Kernels in SVM? |
| What is Cross-Validation? |
| What is Bias in Machine Learning? |
| What is F1 score? How would you use it? |
| What is a Neural Network? |
| What are Loss Function and Cost Functions? Explain the key Difference Between them? |
| What is Ensemble learning? |
| What is a Random Forest? How does it work? |
| What is Collaborative Filtering? And Content-Based Filtering? |
| What is Clustering? |
| What are Recommender Systems? |
| What is P-value? |
| What are Parametric and Non-Parametric Models? |
| What is Reinforcement Learning? |
| Explain SVM Algorithm in Detail |
| Explain the Difference Between Classification and Regression? |
| Explain Correlation and Covariance? |
| Why was Machine Learning Introduced? |
| How to Tackle Overfitting and Underfitting? |
| How do you make sure which Machine Learning Algorithm to use? |
| How to Handle Outlier Values? |
| How can you select K for K-means Clustering? |
| How do check the Normality of a dataset? |
| Can logistic regression use for more than 2 classes? |
17 November 2020
#Machine_Learning
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