In this tutorial, you will learn how to create a Neural Network model in R. 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 In this tutorial, you'll learn about the use of the apply functions in R, its variants, and a few of its relatives applied to different data structures. Explore data analysis with Python. Pandas DataFrames make manipulating your data easy, from selecting or replacing columns and indices to reshaping your data. Develop web crawlers with Scrapy, a powerful framework for extracting, processing, and storing web data. This tutorial explains how to install, run, and use Jupyter Notebooks for data science, including tips, best practices, and examples. In this tutorial, you'll learn how to use predictive analytics to classify song genres. In this tutorial, you'll learn about the basics of Hypothesis Testing and its relevance in Machine Learning. In this tutorial, learn Decision Tree Classification, attribute selection measures, and how to build and optimize Decision Tree Classifier using Python Scikit-learn package. Learn what Vision API is and what are all the things that it offers. By the end of this tutorial, you will also learn how you can call Vision API from your Python code. R Tutorial on Reading and Importing Excel Files into R. Understand how to read and import spreadsheet files using basic R and packages. In this tutorial, you will get a glimpse of encoding techniques along with
some advanced references that will help you tackle categorical variables. The best Python IDEs for data science that make data analysis and machine learning easier! This tutorial will introduce you to the concept of object detection in Python using OpenCV library and how you can utilize it to perform tasks like Facial detection.