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…”

Tabla de Contenidos: “…-- Grasping Python's Core Philosophy -- Contributing to data science -- Discovering present and future development goals -- Working with Python -- Getting a taste of the language -- Understanding the need for indentation -- Working at the command line or in the IDE -- Performing Rapid Prototyping and Experimentation -- Considering Speed of Execution -- Visualizing Power -- Using the Python Ecosystem for Data Science -- 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 -- Chapter 3 Setting Up Python for Data Science…”

Tabla de Contenidos: “…Evaluating the integral -- Case 3: Distinct quadratic factors -- Setting up partial fractions -- Solving for unknowns A, B, and C -- Evaluating the integral -- Case 4: Repeated quadratic factors -- Setting up partial fractions -- Solving for unknowns A, B, C, and D -- Evaluating the integral -- Beyond the Four Cases: Knowing How to Set Up Any Partial Fraction -- Integrating Improper Rationals -- Distinguishing proper and improper rational expressions -- Trying out an example -- Part 5 Applications of Integrals -- Chapter 12 Forging into New Areas: Solving Area Problems -- Breaking Us in Two -- Improper Integrals -- Getting horizontal -- Going vertical -- Handling asymptotic limits of integration -- Piecing together discontinuous integrands -- Finding the Unsigned Area of Shaded Regions on the xy-Graph -- Finding unsigned area when a region is separated horizontally -- Crossing the line to find unsigned area -- Calculating the area under more than one function -- Measuring a single shaded region between two functions -- Finding the area of two or more shaded regions between two functions -- The Mean Value Theorem for Integrals -- Calculating Arc Length -- Chapter 13 Pump Up the Volume: Using Calculus to Solve 3-D Problems -- Slicing Your Way to Success -- Finding the volume of a solid with congruent cross sections -- Finding the volume of a solid with similar cross sections -- Measuring the volume of a pyramid -- Measuring the volume of a weird solid -- Turning a Problem on Its Side -- Two Revolutionary Problems -- Solidifying your understanding of solids of revolution -- Skimming the surface of revolution -- Finding the Space Between -- Playing the Shell Game -- Peeling and measuring a can of soup -- Using the shell method without inverses -- Knowing When and How to Solve 3-D Problems -- Chapter 14 What's So Different about Differential Equations?…”

Tabla de Contenidos: “…-- L'eau, berceau de la vie -- La production des molécules organiques de la « soupe primordiale » -- Support expérimental de l'apport extraterrestre -- Comment la matière peut-elle se mettre à vivre ? …”

Tabla de Contenidos: “…Working with production data -- Challenges and constraints in loading production data -- Generating test data -- Importing test data -- Data load automation -- Handling relationships -- Considerations for test-data management -- Protecting sensitive data with data masking -- Understanding data masking -- Implementing data masking -- Compliance and best practices -- Tools and resources -- Summary -- Chapter 12: Salesforce DevOps Tools - Gearset -- Technical requirements -- Gearset overview -- Gearset's strengths -- Gearset's weaknesses -- Summary -- Chapter 13: Copado -- An overview of Copado -- Platform -- Version control -- Build integration -- Deployment -- Environments -- Change management -- Administration -- Robotic testing -- Understanding the strengths of Copado -- Exploring the weaknesses of Copado -- Summary -- Chapter 14: Salesforce DevOps Tools - Flosum -- Technical requirements -- A Flosum overview -- Deployments -- The Trust Center -- Backup and Data Migrator -- Integrations and customizations -- Flosum's strengths -- Flosum's weaknesses -- Summary -- Chapter 15: AutoRABIT -- An overview of AutoRABIT -- AutoRABIT platform overview -- ARM -- AutoRABIT Vault for data protection -- AutoRABIT CodeScan for static analysis -- Understanding the strengths of AutoRABIT -- Exploring the weaknesses of AutoRABIT -- Summary -- Chapter 16: Other Salesforce DevOps Tools -- Salesforce DevOps Center -- Other commercial tools -- Salto -- Panaya -- Prodly -- Elements.cloud -- Opsera -- Open source tools -- Happy Soup -- SFDX-Hardis -- DX@Scale -- CumulusCI -- Summary -- Chapter 17: Conclusion -- A summary of Salesforce DevOps -- The field of Salesforce DevOps -- Key learnings from Salesforce DevOps tools -- Looking ahead - the future of Salesforce DevOps -- Common pitfalls to avoid -- Implementing a successful Salesforce DevOps strategy…”

Tabla de Contenidos: “…-- Chapter 8 Disks and Drives -- The Mass Storage System -- Reviewing mass storage types -- Measuring mass storage -- Connecting mass storage -- Removable Media -- Adding storage -- Ejecting storage media -- Unmounting an external drive -- Mass Storage Alphabet Soup -- Handing out drive letters -- Exploring drive icons and names -- Checking drive capacity…”

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