{"product_id":"productive-and-efficient-data-science-with-python-best-practices-guide-to-implementing-aiops-9781484281208","title":"Productive and Efficient Data Science with Python: Best Practices Guide to Implementing Aiops","description":"Chapter 1: What is Productive and Efficient Data Science?Chapter Goal: To introduce the readers with the concept of doing data science tasks efficiently and more productively and illustrating potential pitfalls in their everyday work.No of pages - 10Subtopics- Typical data science pipeline- Short examples of inefficient programming in data science- Some pitfalls to avoid- Efficiency and productivity go hand in hand- Overview of tools and techniques for a productive data science pipeline- Skills and attitude for productive data science\u003cbr\u003eChapter 2: Better Programming Principles for Efficient Data ScienceChapter Goal: Help readers grasp the idea of efficient programming techniques and how they can be applied to a typical data science task flow.No of pages - 15Subtopics- The concept of time and space complexity, Big-O notation- Why complexity matters for data science- Examples of inefficient programming in data science tasks- What you can do instead- Measuring code execution timing\u003cbr\u003eChapter 3: How to Use Python Data Science Packages more ProductivelyChapter Goal: Illustrate handful of tricks and techniques to use the most well-known Python data science packages - Numpy, Pandas, Matplotlib, Seaborn, Scipy - more productively.No of pages - 20Subtopics- Why Numpy is faster than regular Python code and how much- Using Numpy efficiently- Using Pandas productively- Matplotlib and Seaborn code for and productive EDA- Using SciPy for common data science tasks\u003cbr\u003eChapter 4: Writing Machine Learning Code More ProductivelyChapter Goal: Teach the reader about writing efficient and modular machine learning code for productive data science pipeline with hands-on examples using Scikit-learn.No of pages - 15Subtopics- Why modular code for machine learning and deep learning- Scikit-learn tools and techniques- Systematic evaluation of Scikit-learn ML algorithms in automated fashion- Decision boundary visualization with custom function- Hyperparameter search in Scikit-learn\u003cbr\u003eChapter 5: Modular and Productive Deep Learning CodeChapter Goal: Teach the reader about mixing modular programming style in deep learning code with hands-on examples using Keras\/TensorFlow.No of pages - 25Subtopics- Why modular code and object-oriented style for deep learning- Wrapper functions with Keras for faster deep learning experimentations- A single function to streamline image classification task flow- Visualize activation functions of neural networks- Custom callback functions in Keras and their utilities- Using Scikit-learn wrapper for hyperparameter search in Keras\u003cbr\u003eChapter 6: Build Your Own Machine Learning Estimator\/PackageChapter Goal: Illustrate how to build a new Python machine learning module\/package from scratch.No of pages - 15Subtopics- Why write your own ML package\/module?- A simple example vs. a data scientist's example- A good, old Linear Regression estimator - with a twist- How do you start building?- Add utility functions- Do more with object-oriented approach\u003cbr\u003eChapter 7: Some Cool Utility PackagesChapter Goal: Introduce the readers to the idea of executing data science tasks efficiently by going beyond traditional stack and utilizing exciting, new libraries.No of pages - 20Subtopics- The great Python\u003cbr\u003e\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Apress\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 07\/27\/2022\u003cbr\u003e\u003cb\u003eISBN:\u003c\/b\u003e 9781484281208\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 290\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 1.55lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 10.00h x 7.00w x 0.84d","brand":"Tirthajyoti Sarkar","offers":[{"title":"Default Title","offer_id":42277137612981,"sku":"9781484281208","price":55.24,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0473\/0804\/6492\/products\/img_fa93d4b4-863d-4b60-aedd-2937e80f83d1.jpg?v=1657595175","url":"https:\/\/pastforward.org\/products\/productive-and-efficient-data-science-with-python-best-practices-guide-to-implementing-aiops-9781484281208","provider":"Past Forward","version":"1.0","type":"link"}