Machine Learning

All the articles related to supervised and unsupervised machine learning

• What is the difference between KNN and K-means Clustering?
• Why would I need a confusion matrix?
• How would you import a decision tree classifier in sklearn?
• What is transfer learning?
• What is batch normalization?
• What is an Epoch?
• What is a Batch?
• What do you understand by feature vectors?
• What do you know about Autoencoders?
• What are Eigenvectors and Eigenvalues?
• How would you develop a model to identify plagiarism?
• What do you know about Autoencoders?
• Differentiate between Cluster and Systematic Sampling?
• What are tensors?
• How to standardize variables?
• How to fine tune random forest model?
• What is the benefit of dimensionality reduction?
• What is dimensionality reduction?
• How is Amazon Able to Recommend Other Things to Buy? How Does the Recommendation Engine Work?
• what is backpropagation?
• what is scoring or inferencing?
• How Can You Choose a Classifier Based on a Training Set Data Size?
• When Overfitting can be useful?
• what is pipeline?
• how to split the data?
• what is ROC curve?
• what is PCA - principal component analysis?
• what is hyperparameters?
• What is hot encoding?
• what is the Train/Test split methodology?
• How to know whether your model is suffering from the problem of Exploding Gradients?
• What is a model Learning Rate? Is a high learning rate always good?
• What does NLP stand for?
• What is survivorship bias?
• What is an RNN (recurrent neural network)?
• What are Recommender Systems?
• What Are Some Methods of Reducing Dimensionality?
• what are the different types of nodes in Decision Trees?
• What Is Entropy in a Decision Tree Algorithm?
• What Is Deep Learning?
• How would you detect Overfitting in Linear Models?
• what is regularization?
• What is gradient boosting estimator?
• How can you avoid overfitting your model?
• What are recommender systems?
• what is the difference between True Positive, True Negative, False Positive – Type 1 Error and False Negative – Type 2 Error?
• Explain Correlation and Covariance?
• What is Semi-supervised Machine Learning?
• What is the Null Hypothesis in regression?
• how to know whether you have collected enough data to train your machine learning model or not?
• when creating dummy variables for a categorical variable, why do we need to discard one of them?
• Why Naive Bayes is called Naive?
• what is the difference between supervised and unsupervised learning ?