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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 ?
Unsupervised
Supervised
- What is ‘training set’ and ‘test set’ in a machine learning model? how much data will you allocate for your training, validation, and test sets?
- What Is Logistic Regression?
- How do you calculate the MSE in a linear regression model?
- What is F1-Score
- What is recall?
- What is classification?
- What is learning rate?
- What is loss functions?
- What is information gain ?
- What is the difference between a binary classifier and a multinomial classifier?
- Is Naïve Bayes bad?
- What is k-fold cross-validation?
- What Are the Applications of Supervised Machine Learning in Modern Businesses?
- What is ensemble learning?
- What is a Decision Boundary?
- Explain the Random Forest Model
- What are the assumptions you need to take before starting with linear regression?
- List out the disadvantages of the Decision Trees.
- What kind of regression models are there?
- What kind of models are supervised learning?
- What is regression?
- Are Decision Trees affected by the outliers? Explain.
- What is the term used to describe the case when the predictors in a multiple regression model are correlated?
- Which should be preferred among Gini impurity and Entropy?
- List down the advantages of the Decision Trees.
- What Is Pruning in a Decision Tree Algorithm?
- What is Root Mean Squared Error (RMSE)?
Statistics
- What is differences between samples and population?
- What-is-a-p-value-what-is-the-significance-of-p-value
- What is normalizing?
- In experimental design, is it necessary to do randomization?
- What is Box-Cox transformation?
- What is the difference between an error and a residual error?
- What is a normal distribution?
- Why correlation is not causation?
- What is differences between mean, median, and mode?
Deep Learning
- What is Convolutional neural networks?
- Why is TensorFlow considered important in Data Science?
- What is the full form of LSTM? What is its function?
- What is GAN?
- What is an Activation function?
- How beneficial is dropout regularization in deep learning models? Does it speed up or slow down the training process, and why?