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Tabla de Contenidos: “…Bike 101 -- Origins -- Anatomy of a Bicycle -- Brakes -- Brake Lever -- Cassette -- Chain -- Chainring -- Derailleurs -- Frame -- Gear Shifts -- Handlebars -- Pedals -- Saddle -- Tires -- Variants -- BMX -- Fixie -- Folding -- Penny Farthing -- Recumbent -- Tall -- Tandem -- Tricycle -- Unicycle -- Just Hack It -- Summary -- Chapter 2. …”

Tabla de Contenidos: “…Understanding cells -- Adding documentation cells -- Using other cell types -- Understanding the Use of Indentation -- Adding Comments -- Understanding comments -- Using comments to leave yourself reminders -- Using comments to keep code from executing -- Getting Help with the Python Language -- Working in the Cloud -- Using the Kaggle datasets and kernels -- Using the Google Colaboratory -- Chapter 4 Leveraging a Deep Learning Framework -- Presenting Frameworks -- Defining the differences -- Explaining the popularity of frameworks -- Defining the deep learning framework -- Choosing a particular framework -- Working with Low-End Frameworks -- Caffe2 -- Chainer -- PyTorch -- MXNet -- Microsoft Cognitive Toolkit/CNTK -- Understanding TensorFlow -- Grasping why TensorFlow is so good -- Making TensorFlow easier by using TFLearn -- Using Keras as the best simplifier -- Getting your copy of TensorFlow and Keras -- Fixing the C++ build tools error in Windows -- Accessing your new environment in Notebook -- Part 2 Considering Deep Learning Basics -- Chapter 5 Reviewing Matrix Math and Optimization -- Revealing the Math You Really Need -- Working with data -- Creating and operating with a matrix -- Understanding Scalar, Vector, and Matrix Operations -- Creating a matrix -- Performing matrix multiplication -- Executing advanced matrix operations -- Extending analysis to tensors -- Using vectorization effectively -- Interpreting Learning as Optimization -- Exploring cost functions -- Descending the error curve -- Learning the right direction -- Updating -- Chapter 6 Laying Linear Regression Foundations -- Combining Variables -- Working through simple linear regression -- Advancing to multiple linear regression -- Including gradient descent -- Seeing linear regression in action -- Mixing Variable Types -- Modeling the responses -- Modeling the features…”

Tabla de Contenidos: “…Chapter 3 Creating a Data Science Lab of Your Own -- Considering the Analysis Platform Options -- Using a desktop system -- Working with an online IDE -- Considering the need for a GPU -- Choosing a Development Language -- Obtaining and Using Python -- Working with Python in this book -- Obtaining and installing Anaconda for Python -- Defining a Python code repository -- Working with Python using Google Colaboratory -- Defining the limits of using Azure Notebooks with Python and R -- Obtaining and Using R -- Obtaining and installing Anaconda for R -- Starting the R environment -- Defining an R code repository -- Presenting Frameworks -- Defining the differences -- Explaining the popularity of frameworks -- Choosing a particular library -- Accessing the Downloadable Code -- Chapter 4 Considering Additional Packages and Libraries You Might Want -- Considering the Uses for Third-Party Code -- Obtaining Useful Python Packages -- Accessing scientific tools using SciPy -- Performing fundamental scientific computing using NumPy -- Performing data analysis using pandas -- Implementing machine learning using Scikit-learn -- Going for deep learning with Keras and TensorFlow -- Plotting the data using matplotlib -- Creating graphs with NetworkX -- Parsing HTML documents using Beautiful Soup -- Locating Useful R Libraries -- Using your Python code in R with reticulate -- Conducting advanced training using caret -- Performing machine learning tasks using mlr -- Visualizing data using ggplot2 -- Enhancing ggplot2 using esquisse -- Creating graphs with igraph -- Parsing HTML documents using rvest -- Wrangling dates using lubridate -- Making big data simpler using dplyr and purrr -- Chapter 5 Leveraging a Deep Learning Framework -- Understanding Deep Learning Framework Usage -- Working with Low-End Frameworks -- Chainer -- PyTorch -- MXNet…”