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Welcome to sudo-code
Formulae Cheat Sheet to Prepare for Machine Learning Specialty Remember how to write Confusion Matrix Know how to write confusion matrix when Actual and Predicted are swapped Write down both versions of confusion matrix in a rough sheet provided as soon as you start exam Basic Formulae for Classification Precision, Recall and Specificity $$ Precision = Positive Prediction Value (PPV) = \frac{TP}{TP+FP} $$ $$ Recall = Sensitivity = True Positive Rate (TPR) = \frac{TP}{TP+FN} $$ $$ Specificity = True Negative Rate (TNR) = \frac{TN}{TN+FP} $$...
What are activation functions ? Activation functions are the key to Neural Networks (NN). They are the recipe to learn non-linear relationships in data, without them NNs would just be linear in nature. If you know the basics of logistic regression, you’ll understand the statement I made. I am planning to write another blog to cover activation functions from basics, therefore the focus here is just to compare softmax and sigmoid activation functions....
We need to learn about bias and variance in order to understand how to fix underfitting and overfitting of model. Spend enough time to read and understand, everything till the end of the blog, where you get to know how to apply the concepts (helpful for MLS-C01 exam too!) What are Bias and Variance ? Welcome to the world of bias and variance. It may be confusing at first, but by end of the blog, you’ll have full clarity....
Courtesy: Photo by Green Chameleon on Unsplash What is MLS-C01 and how is it helpful ? If you crack the MLS-C01 exam, I can assure you, it can help you in your role at your current company, may be a promotion or some other benefit. It definitely helped me to set myself apart from the crowd in my company, and helped me get a promotion as well. It depends on person to person and opportunities in company....
What are hyperparameters ? In simple terms, hyperparameters are a set of knobs you can tune before starting the learning process in machine learning. When set to a specific values, the model has a specific performance. When the hyperparameters are set to new values, the model gets new performance values. What is performance of a model? In any machine learning process, we want to optimize the objective-function: a fancy name for a function that evaluates model predictions v/s values provided during training....