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An important question that might arise is, how can I assess how well my model is performing? Just like the teacher assesses your accuracy by verifying your answers against the desired answers, you assess the model’s accuracy by comparing the values predicted by the model with the actual values. In machine learning lingo, a ‘ cost function‘ is used to evaluate the performance of a model. So in crude words, tests are used to analyze how well you have performed in class. If you haven’t(as unlikely as it is), you need to improve your accuracy and attempt again. If you have managed to maintain your accuracy and have shot your scores over a certain benchmark, you have passed. How does your teacher assess whether you have studied throughout the academic year or not? She takes a test at the end and grades your performance by cross-checking your answers against the desired answers. ML | Label Encoding of datasets in Python.Regression and Classification | Supervised Machine Learning.ML | One Hot Encoding to treat Categorical data parameters.Introduction to Hill Climbing | Artificial Intelligence.Best Python libraries for Machine Learning.Activation functions in Neural Networks.
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Elbow Method for optimal value of k in KMeans.Decision Tree Introduction with example.Linear Regression (Python Implementation).Removing stop words with NLTK in Python.ISRO CS Syllabus for Scientist/Engineer Exam.ISRO CS Original Papers and Official Keys.GATE CS Original Papers and Official Keys.