{"product_id":"learn-all-about-scipy-9798395136541","title":"Learn all about SciPy","description":"\u003cp\u003e • Author(s): Innoware Pjp\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Computers \u0026amp; Technology\u003c\/p\u003e\u003cp\u003e\u003cb\u003eLearn all about SciPy\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003eSciPy is an open-source library built on top of NumPy, another fundamental library in the Python scientific ecosystem. SciPy expands upon NumPy by offering additional functionality and tools for scientific computing. It provides a collection of modules, each focusing on specific aspects of scientific computation, including optimization, linear algebra, interpolation, signal processing, statistics, and more. With its extensive capabilities, SciPy serves as a valuable resource for researchers, engineers, and data scientists. \u003cp\u003e\u003c\/p\u003e\u003cb\u003eThe book covers the following: \u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e\u003cb\u003e1. Introduction\u003c\/b\u003e\u003cbr\u003e1.1 The significance of scientific computing in various disciplines\u003cbr\u003e1.2 Overview of SciPy and its role in Python's scientific ecosystem\u003cbr\u003e1.3 Setting up the development environment \u003cp\u003e\u003c\/p\u003e\u003cb\u003e2. NumPy Foundations\u003c\/b\u003e\u003cbr\u003e2.1 Understanding NumPy arrays and their advantages\u003cbr\u003e2.2 Array creation, manipulation, and indexing\u003cbr\u003e2.3 Basic mathematical operations with arrays\u003cbr\u003e2.4 Broadcasting and vectorization\u003cbr\u003e2.5 Exploring common NumPy functions \u003cp\u003e\u003c\/p\u003e\u003cb\u003e3. SciPy Basics\u003c\/b\u003e\u003cbr\u003e3.1 Introduction to SciPy's subpackages and their functionalities\u003cbr\u003e3.2 Handling multidimensional data with SciPy\u003cbr\u003e3.3 Data input\/output operations\u003cbr\u003e3.4 Basic statistical operations using SciPy\u003cbr\u003e3.5 Plotting and visualization with Matplotlib \u003cp\u003e\u003c\/p\u003e\u003cb\u003e4. Linear Algebra and Optimization\u003c\/b\u003e\u003cbr\u003e4.1 Linear algebra operations with SciPy\u003cbr\u003e4.2 Solving linear systems of equations\u003cbr\u003e4.3 Matrix decompositions and their applications\u003cbr\u003e4.4 Optimization techniques and algorithms\u003cbr\u003e4.5 Application examples in data fitting and regression \u003cp\u003e\u003c\/p\u003e\u003cb\u003e5. Interpolation and Approximation\u003c\/b\u003e\u003cbr\u003e5.1 Understanding interpolation and its importance in scientific computing\u003cbr\u003e5.2 Different interpolation methods and their characteristics\u003cbr\u003e5.3 Splines and piecewise polynomial interpolation\u003cbr\u003e5.4 Approximation techniques for data smoothing\u003cbr\u003e5.5 Real-world examples of interpolation and approximation \u003cp\u003e\u003c\/p\u003e\u003cb\u003e6. Numerical Integration and Differentiation\u003c\/b\u003e\u003cbr\u003e6.1 Introduction to numerical integration and differentiation\u003cbr\u003e6.2 Techniques for numerical integration using SciPy\u003cbr\u003e6.3 Numerical differentiation methods\u003cbr\u003e6.4 Applications in calculus and physics\u003cbr\u003e6.5 Error analysis and handling numerical instability \u003cp\u003e\u003c\/p\u003e\u003cb\u003e7. Signal and Image Processing\u003c\/b\u003e\u003cbr\u003e7.1 Signal processing concepts and applications\u003cbr\u003e7.2 Filtering and convolution operations\u003cbr\u003e7.3 Fourier analysis and spectral processing\u003cbr\u003e7.4 Image processing techniques with SciPy\u003cbr\u003e7.5 Feature extraction and image enhancement \u003cp\u003e\u003c\/p\u003e\u003cb\u003e8. Sparse Matrix Computations\u003c\/b\u003e\u003cbr\u003e8.1 Understanding sparse matrices and their advantages\u003cbr\u003e8.2 Sparse matrix storage formats\u003cbr\u003e8.3 Sparse matrix operations and algorithms\u003cbr\u003e8.4 Applications in large-scale scientific computations\u003cbr\u003e8.5 Sparse linear systems and eigenvalue problems \u003cp\u003e\u003c\/p\u003e\u003cb\u003e9. Machine Learning with SciPy\u003c\/b\u003e\u003cbr\u003e9.1 Overview of machine learning and its importance\u003cbr\u003e9.2 Integration of SciPy with scikit-learn\u003cbr\u003e9.3 Supervised and unsupervised learning algorithms\u003cbr\u003e9.4 Feature extraction and dimensionality reduction\u003cbr\u003e9.5 Model evaluation and validation \u003cp\u003e\u003c\/p\u003e\u003cb\u003e10. Time Series Analysis\u003c\/b\u003e\u003cbr\u003e10.1 Introduction to time series data\u003cbr\u003e10.2 Time series manipulation and preprocessing with SciPy\u003cbr\u003e10.3 Analyzing trends, seasonality, and autocorrelation\u003cbr\u003e10.4 Forecasting techniques using SciPy\u003cbr\u003e10.5 Case studies in financial data analysis and forecasting \u003cp\u003e\u003c\/p\u003e\u003cb\u003e11. Advanced Topics in SciPy\u003c\/b\u003e\u003cbr\u003e11.1 Advanced optimization methods\u003cbr\u003e11.2 Numerical methods for differential equations\u003cbr\u003e11.3 Statistical modeling and hypothesis testing\u003cbr\u003e11.4 Spatial data analysis with SciPy\u003cbr\u003e11.5 High-performance computing with SciPy","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":45550388740247,"sku":"9798395136541","price":2208.0,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798395136541.webp?v=1768585346","url":"https:\/\/atlanticbooks.com\/products\/learn-all-about-scipy-9798395136541","provider":"Atlantic Books","version":"1.0","type":"link"}