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Detalhes do Torrent Para "Udemy - Complete NumPy Masterclass Go from Zero to Hero in Numpy"

Udemy - Complete NumPy Masterclass Go from Zero to Hero in Numpy

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Última verificado: 05-05-2021 06:01:39

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Nome:	Udemy - Complete NumPy Masterclass Go from Zero to Hero in Numpy
Description: This is the  most comprehensive, yet straight-forward course for the Numerical Python (NumPy) on Udemy!  Whether you have never used NumPy before, already know basic a bit of Python, or want to learn about the advanced features of NumPy with Python, this course is for you! In this course we will  teach you NumPy with Python.  With  over 65 lectures  and more than 7.5 hours of video this comprehensive course leaves no stone unturned in teaching you NumPy with Python 3! This course will teach you NumPy in a very practical manner, with every lecture comes a full NumPy programming videos and corresponding Jupyter notebooks that has Python 3 code! Learn in whatever manner is the best for you! Created by Ashwin Pajankar • 20,000+ Students Worldwide, BPB Online + 90 Million Books Sold Last updated 11/2018 English
Video YouTube:
Categoria:	Tutorials
Idioma:	English
Total Size:	3.96 GB
Informações Hash:	739D3E9EA08FDCE0343D766326E40ED715456A1B
Adicionado por:	fclab16
Data adicionada:	2018-12-02 07:51:56
Torrent Status:	Torrent Verified

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Lista de arquivos:

Arquivo	Tamanho
1. Introduction/1. Course Objectives, Audience, and prerequisites.mp4	50.91 MB
1. Introduction/1.1 01 Course Objectives.pdf.pdf	469.12 kB
1. Introduction/2. Course Contents Walkthrough.mp4	29.10 MB
1. Introduction/2.1 02 Course Contents Walkthrough.pdf.pdf	288.04 kB
1. Introduction/3. Please do leave your feedback.mp4	3.66 MB
1. Introduction/4. Scientific Python Ecosystem.mp4	28.32 MB
1. Introduction/4.1 04 Scientific Python Ecosystem.pdf.pdf	289.79 kB
1. Introduction/5. Introduction to NumPy.mp4	19.93 MB
1. Introduction/5.1 05 Introduction to NumPy.pdf.pdf	210.03 kB
1. Introduction/6. PDF of URLs of all the Scientific Python Libraries.html	96.00 B
1. Introduction/6.1 06 URLs of projects in Scientific Python Ecosystem.pdf.pdf	113.46 kB
10. Routines for Random/1. Routines for Random.mp4	32.85 MB
11. Array Manipulation/1. Array Manipulation Routines (split, stack, flip).mp4	189.78 MB
12. Bitwise Operations on NumPy Arrays/1. Bitwise Operations on NumPy Arrays.mp4	21.84 MB
13. Statistical Functions in NumPy/1. Statistical Functions in NumPy.mp4	30.51 MB
14. FFTs/1. FFTs and Inverse FFT.mp4	90.17 MB
14. FFTs/2. Advanced FFTs.mp4	70.16 MB
15. Matrices and Linear Algebra/1. Dot Products.mp4	45.79 MB
15. Matrices and Linear Algebra/2. Vector Dot Product.mp4	19.52 MB
15. Matrices and Linear Algebra/3. Inner Product.mp4	13.83 MB
15. Matrices and Linear Algebra/4. QR Decomposition.mp4	17.20 MB
15. Matrices and Linear Algebra/5. Determining and Solving Linear Equations.mp4	38.40 MB
16. Mathematical and Trigonometric Functions/1. Sin, Cos, Tan.mp4	30.36 MB
16. Mathematical and Trigonometric Functions/2. Sinh, Cosh, Tanh.mp4	18.81 MB
16. Mathematical and Trigonometric Functions/3. Exponent.mp4	18.89 MB
16. Mathematical and Trigonometric Functions/4. Logarithms.mp4	14.96 MB
16. Mathematical and Trigonometric Functions/5. Convolution.mp4	15.38 MB
17. Digital Image Processing with NumPy and Matplotlib/1. What is Digital Image Processing.mp4	58.09 MB
17. Digital Image Processing with NumPy and Matplotlib/10. Logical Operations.mp4	79.91 MB
17. Digital Image Processing with NumPy and Matplotlib/11. Histogram with NumPy and Matplotlib.mp4	126.05 MB
17. Digital Image Processing with NumPy and Matplotlib/2. Image Datasets for Practicals.mp4	43.98 MB
17. Digital Image Processing with NumPy and Matplotlib/2.1 01 Image Datasets Online.pdf.pdf	190.97 kB
17. Digital Image Processing with NumPy and Matplotlib/3. Installing Pillow on Windows and Raspberry Pi.mp4	46.65 MB
17. Digital Image Processing with NumPy and Matplotlib/4. Reading, Displaying, and Saving images on Disk with Matplotlib.mp4	78.39 MB
17. Digital Image Processing with NumPy and Matplotlib/5. NumPy for Image Processing and Computer Vision.mp4	113.77 MB
17. Digital Image Processing with NumPy and Matplotlib/6. Image Statistics.mp4	20.97 MB
17. Digital Image Processing with NumPy and Matplotlib/7. Image Masks.mp4	56.09 MB
17. Digital Image Processing with NumPy and Matplotlib/8. Image Channels.mp4	81.81 MB
17. Digital Image Processing with NumPy and Matplotlib/9. Arithmetic Operations.mp4	79.45 MB
18. File Operations with NumPy/1. Working with .npy files.mp4	32.20 MB
18. File Operations with NumPy/2. Working with .csv files.mp4	26.44 MB
19. Set Operations with NumPy/1. Set Operations with NumPy.mp4	47.67 MB
2. Python 3 on Windows/1. Install Python 3 on Windows.mp4	47.65 MB
2. Python 3 on Windows/2. Verify Python 3 installation on Windows.mp4	46.86 MB
2. Python 3 on Windows/2.1 02 Verifying Installation on Windows.pdf.pdf	155.24 kB
20. Sorting and Counting Routines in NumPy/1. Sorting with NumPy.mp4	17.65 MB
20. Sorting and Counting Routines in NumPy/2. Counting non-zero elements in NumPy Ndarray.mp4	24.15 MB
21. Downloadable Code Bundle/1. Downloadable Code Bundle.html	77.00 B
21. Downloadable Code Bundle/1.1 CodeBundle.zip.zip	3.93 MB
3. Python 3 and Raspberry Pi/1. What is Raspberry Pi.mp4	45.36 MB
3. Python 3 and Raspberry Pi/2. Raspberry Pi Unboxing.mp4	84.53 MB
3. Python 3 and Raspberry Pi/3. Resources for Raspberry Pi Setup.html	54.00 B
3. Python 3 and Raspberry Pi/3.1 02 Web URLs for downloads.pdf.pdf	110.35 kB
3. Python 3 and Raspberry Pi/4. Raspberry Pi Raspbian OS Setup Part 1.mp4	229.20 MB
3. Python 3 and Raspberry Pi/5. Raspberry Pi Raspbian OS Setup Part 2.mp4	183.94 MB
3. Python 3 and Raspberry Pi/6. Remotely accessing Pi with VNC.mp4	106.32 MB
3. Python 3 and Raspberry Pi/7. Python on Raspberry Pi.mp4	78.73 MB
3. Python 3 and Raspberry Pi/8. List of Linux Commands used in Raspberry Pi Setup.html	90.00 B
3. Python 3 and Raspberry Pi/8.1 06 Linux Commands used in the Course.pdf.pdf	158.06 kB
4. Basics of Python 3/1. Hello World program on Windows.mp4	58.66 MB
4. Basics of Python 3/2. Hello World program on Raspberry Pi.mp4	117.06 MB
4. Basics of Python 3/3. Python 3 Interpreter vs Script Mode.mp4	44.28 MB
4. Basics of Python 3/4. Exploring IDLE.mp4	69.85 MB
4. Basics of Python 3/5. What platform to use.mp4	71.11 MB
5. Python Package Index and pip/1. Introduction to PyPI and pip.mp4	31.06 MB
5. Python Package Index and pip/2. pip on Windows.mp4	62.92 MB
5. Python Package Index and pip/3. pip on Raspberry Pi.mp4	82.27 MB
6. NumPy and Matplotlib installation/1. Install NumPy and Matplotlib on Windows.mp4	46.65 MB
6. NumPy and Matplotlib installation/2. Install NumPy and Matplotlib on Raspberry Pi.mp4	62.89 MB
6. NumPy and Matplotlib installation/2.1 02 Installing NumPy and Matplotlib on Raspberry Pi.pdf.pdf	155.30 kB
7. Jupyter/1. What is Jupyter.mp4	103.34 MB
7. Jupyter/2. Install Jupyter on Windows.mp4	53.23 MB
7. Jupyter/3. Install Jupyter on Raspberry Pi.mp4	62.67 MB
7. Jupyter/4. Install PuTTY on Windows.mp4	37.39 MB
7. Jupyter/5. Remotely connect to a Jupyter notebook.mp4	52.75 MB
7. Jupyter/6. A brief Tour of Jupyter.mp4	153.28 MB
7. Jupyter/7. List of commands and other resources used in this section.html	79.00 B
7. Jupyter/7.1 07 Jupyter Installation and Remote Connection.pdf.pdf	162.99 kB
8. Getting Started with NumPy/1. Creating N-dimensional arrays, indexing, and slicing.mp4	129.88 MB
8. Getting Started with NumPy/2. NumPy Ndarrays Properties.mp4	42.76 MB
8. Getting Started with NumPy/3. NumPy Mathematical and Scientific Constants.mp4	16.41 MB
8. Getting Started with NumPy/4. NumPy Data Types.html	75.00 B
8. Getting Started with NumPy/4.1 NumPy Datatypes.pdf.pdf	162.40 kB
9. Array Creation Routines and Matplotlib/1. Zeroes and Ones.mp4	48.28 MB
9. Array Creation Routines and Matplotlib/2. Matrices.mp4	31.63 MB
9. Array Creation Routines and Matplotlib/3. What is Matplotlib.mp4	15.64 MB
9. Array Creation Routines and Matplotlib/3.1 03 Matplotlib.pdf.pdf	281.15 kB
9. Array Creation Routines and Matplotlib/4. NumPy Numerical Ranges and Matplotlib.mp4	102.21 MB
[FreeCourseLab.com].url	126.00 B

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Udemy - Complete NumPy Masterclass Go from Zero to Hero in Numpy