In this tutorial to deep learning in R with RStudio's keras package, you'll learn how to build a Multi-Layer Perceptron (MLP). This Keras tutorial introduces you to deep learning in Python: learn to preprocess your data, model, evaluate and optimize neural networks. This Python for Finance tutorial introduces you to algorithmic trading, and much more. Learn about anti-patterns, execution plans, time complexity, query tuning, and optimization in SQL.
Learn how to build a neural network and how to train, evaluate and optimize it with TensorFlow Explore data analysis with Python. Pandas DataFrames make manipulating your data easy, from selecting or replacing columns and indices to reshaping your data. This tutorial explains how to install, run, and use Jupyter Notebooks for data science, including tips, best practices, and examples. The best Python IDEs for data science that make data analysis and machine learning easier! In this tutorial, you’ll learn how to create publishable and reproducible data science studies on Kyso’s platform, using interactive plotly visualizations.
In this tutorial, you'll get an overview of Artificial Intelligence (AI) and take a closer look in what makes Machine Learning (ML) and Deep Learning different.
In this tutorial, the reader will learn the Monte Carlo methodology and its applications in data science, like integral approximation, and parameter estimation. Practice autocorrelation in R by using course material from DataCamp's Introduction to Time Series Analysis course. In this tutorial, you'll learn how to create subqueries in SQL to better analyze and report data. In this tutorial, you'll learn with the help of an example how "Contingency Analysis" or "Chi-square test of independence" works and also how efficiently we can perform it using R. Networks today are part of our everyday life. Let's learn how to visualize and understand a social network in Python using Networks.