Tutorials
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- Generative AI and NLPTopic Modeling with Gensim (Python)Topic Modeling is a technique to understand and extract the hidden topics from large volumes of text. Latent Dirichlet Allocation(LDA) is an algorithm for topic modeling, which has excellent implementations in the Python's Gensim package. This tutorial tackles the problem of finding the optimal number of topics.
- Pythonpdb – How to use Python debuggerpdb, short for python debugger is a standard built-in module used to debug python code interactively. You can set breakpoints, see variable values, step inside routines, test run code, etc once you enter the pdb. This tutorial demonstrates the best practices of using the python debugger and the new breapoint() feature.
- Machine LearningCaret Package – A Practical Guide to Machine Learning in RUsing caret package, you can build all sorts of machine learning models. In this tutorial, I explain the core features of the caret package and walk you through the step-by-step process of building predictive models. Be it logistic reg or adaboost, caret helps to find the optimal model in the shortest possible time.
- Practice exercises101 NumPy Exercises for Data Analysis (Python)The goal of the numpy exercises is to serve as a reference as well as to get you to apply numpy beyond the basics. The questions are of 4 levels of difficulties with L1 being the easiest to L4 being the hardest.
- PythonNumpy Tutorial Part 2 – Vital Functions for Data AnalysisThis is part 2 of the mega numpy tutorial. In this part, I go into the details of the advanced features of numpy arrays that are essential for data analysis and manipulations.
- PythonNumpy Tutorial – Your first numpy guide to build python coding foundationsThis is part 1 of the numpy tutorial covering all the core aspects of performing data manipulation and analysis with numpy's ndarrays. Numpy is the most basic and a powerful package for data manipulation and scientific computing in python.
- PythonPython Regular Expressions Tutorial and Examples: A Simplified GuideRegular expressions, also called regex, is a syntax or rather a language to search, extract and manipulate specific string patterns from a larger text. In python, it is implemented in the re module. You will first get introduced to the 5 main features of the re module and then see how to create common regex in python.
- Machine LearningEvaluation Metrics for Classification Models – How to measure performance of machine learning models?Computing just the accuracy to evaluate a classification model is not enough. This tutorial shows how to build and interpret the evaluation metrics.
- Machine LearningLogistic Regression – A Complete Tutorial With Examples in RLearn the concepts behind logistic regression, its purpose and how it works. This is a simplified tutorial with example codes in R. Logistic Regression Model or simply the logit model is a popular classification algorithm used when the Y variable is a binary categorical variable.
- Statistics and MathHow to implement common statistical significance tests and find the p value?Learn the purpose, when to use and how to implement statistical significance tests (hypothesis testing) with example codes in R. How to interpret P values for t-Test, Chi-Sq Tests and 10 such commonly used tests.
- Machine LearningComplete Introduction to Linear Regression in RLearn how to implement linear regression in R, its purpose, when to use and how to interpret the results of linear regression, such as R-Squared, P Values.