In this tutorial, you'll learn how to construct and implement Convolutional Neural Networks (CNNs) in Python with the TensorFlow framework. Learn how to read and import Excel files in Python, write data to these spreadsheets, and find the best packages to do this.
Learn what variable scopes are all about and get familiar with the 'LEGB' rule. You will also deal with scenarios where you'll get to see the global and nonlocal keywords in action. Learn about the different types of docstrings and various docstring formats like Sphinx, Numpy and Pydoc. In this tutorial, you'll learn all about R variables including how to define variables, remove variables, and much more. This is a beginner guide that is designed to save yourself a headache and valuable time if you decide to install R yourself. Learn how you can leverage the capability of a simple Python Print function in various ways with the help of examples. Wondering whether you should use Python or R for data analysis? You’ve come to the right place.
learning data science+5
Learn about Markov Chains, their properties, transition matrices, and implement one yourself in Python! In this tutorial, you'll learn about the statistical concepts behind survival analysis and you'll implement a real-world application of these methods in R.
Learn about Logistic Regression, its basic properties, and build a machine learning model on a real-world application in Python. This Keras tutorial introduces you to deep learning in Python: learn to preprocess your data, model, evaluate and optimize neural networks. In this tutorial, you will learn how to train generative models to compose music in TensorFlow 2.0. This Python for Finance tutorial introduces you to algorithmic trading, and much more.