Home
Search results “Python timeit magic”
Learn Jupyter Notebooks (pt.2) %Timeit Magic Function
 
07:37
In this video, I briefly describe magic functions and go into how the Timeit function works, plus some optimization tips! IPython docs on magic functions: https://ipython.org/ipython-doc/3/interactive/magics.html
Views: 6479 Mark Jay
14   Timeit Magic Function Jupyter Notebook
 
03:05
Published on May 13 2018: In this video, we will learn about the timeit magic function in Jupyter Notebook In the previous video, we learnt about the time magic function in Jupyter Notebook Code used in the video: %%timeit x=range(10000) max(x) %timeit {1 for i in xrange(10*1000000)} Previous Video: https://youtu.be/rmaYFfXIhZU Additional Reading material: NA SUBSCRIBE to learn more about Power BI,Power Query, Power Pivot, Excel,SQL Server and Python!! https://www.youtube.com/channel/UCYYHFZpm5GbaOmQKDNSTGLw Our Playists: SQL Playlist :https://goo.gl/PS5Ep6 DAX PlayList : https://goo.gl/S4W41D Power BI PlayList: https://goo.gl/dXxvnB Power Query Playlist: https://goo.gl/5QS7P4 Getting Started with Power BI:https://goo.gl/GHakLZ Getting Started with Python: https://goo.gl/n24P3w Data Science With Python:https://goo.gl/PeYCR5 ABOUT DAGDOO: Website: Home Page: http://www.dagdoo.org/ Power BI Tutorials: http://www.dagdoo.org/excel-learning/tutorial-power-bi-desktop/ Questions? Comments and SUGESTIONS? You will find me here: Twitter: @dagdooe Category: Science & Technology License: Standard YouTube License
Views: 282 Learn 2 Excel
Timeit Module - Intermediate Python Programming p.6
 
11:28
Welcome to part 6 of the intermediate Python programming tutorial series. In this part, we're going to talk about the timeit module. The idea of the timeit module is to be able to test snippets of code. In our previous tutorial, we were talking about list comprehension and generators, and the difference between the two of them (speed vs memory) was explained. Using the timeit module, I will illustrate this. https://pythonprogramming.net https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex
Views: 26279 sentdex
Special magic/dunder method, operator overloading, polymorphism : Python tutorial 202
 
22:29
Guys please help this channel to reach 20,000 subscribers. I'll keep uploading quality content for you. Python is easy programming language to learn and anyone can learn it, and these tutorials are 100% free in hindi. You can share this playlist with your brother, sisters and friends. This will surely add some values to their life. Complete Playlist link - https://www.youtube.com/playlist?list=PLwgFb6VsUj_lQTpQKDtLXKXElQychT_2j If you follow this complete playlist of python tutorial surely you will learn everything about python programming language. This video is all about special magic/dunder methods, operator overloading, polymorphism. Source Code Link - https://www.dropbox.com/s/c8vqlzxhx2ksp61/poly.py?dl=0
Views: 3326 Harshit vashisth
Magic Methods in Python
 
07:21
An intro to magic methods in Python. Enjoy! Reference: http://www.rafekettler.com/magicmethods.html
Let's Code Python: timeit
 
20:33
Today we'll look at the timeit module, which allows you to conveniently run performance tests on blocks of code.
Views: 929 TigerhawkT3
Episode 2: How to use Jupyter Notebook's Magic Commands?
 
15:07
Refer this for more - http://ipython.readthedocs.io/en/stable/interactive/magics.html
Views: 480 GeekGirl64
3. Basic Python - IPython Notebook Tutorial
 
09:59
This tutorial covers working with code cells and IPython magic and getting help about your objects using object? , object?? and help(object). Other IPython magic codes in this tutorial are: %quickref, %lsmagic %timeit and %%timeit. Finally, we cover In[] and Out[] lists and the underscore for accessing the last output. This is open source, Github/NBViwer: http://nbviewer.ipython.org/github/twistedhardware/mltutorial/blob/master/notebooks/IPython-Tutorial/3%20-%20Basic%20Python.ipynb
Views: 10517 Roshan
Decorators, timeit, and doctest
 
15:14
Can decorators be used to test functions? How? Why would you do this? Why not?
Views: 242 harrisonishable
[Python] Temps de calcul - Module timeit
 
03:33
Mesurer le temps d'exécution d'une fonction.
Views: 384 Python au lycée
Jupyter demo 7—Python functions
 
10:41
An overview of Python functions, to complement the course module "Get Data Off the Ground with Python." Join the online module: http://go.gwu.edu/engcomp1 Recorded at: https://ibleducation.com
Views: 324 Lorena Barba
Python Decorators Tutorial
 
10:25
In this tutorial, I explain decorators in a very simple way by going over how to measure execution time of function using decorators. They serve as a wrapper to original function but does a wonderful job of avoiding code duplication and not cluttering original code with additional logic. Code in this tutorial is available here: https://github.com/codebasics/py/blob/master/Advanced/decorators.py Website: http://codebasicshub.com/ Facebook: https://www.facebook.com/codebasicshub Twitter: https://twitter.com/codebasicshub Google +: https://plus.google.com/106698781833798756600 Patreon: https://www.patreon.com/codebasics
Views: 36885 codebasics
11-Magic Functions | Object Oriented Programming With Python
 
11:42
This session tells you about some of the many magical functions available in python to make your work easy.
Views: 99 CodeBox
Using Timeit for measuring code snippets
 
00:49
Measuring String concatenation performance using Python module Timeit. Source code: https://drive.google.com/file/d/0Bzz3FVz0lhCVWVdHMHhXRXFuUjA/view?usp=sharing
Views: 487 Py Minute
Analysis 5 | Timeit 1
 
07:01
Python, how to user the timeit module to time list and other code This is part of my video course: https://goo.gl/ghFZar Code/Slides link: https://goo.gl/ZNGPMU These videos are to help you when reading the ebook: "Problem Solving with Algorithms and Data Structures using Python" at ebook: https://goo.gl/1GJCgt images of the ebook and some code from the book are attributed to this book by the Authors Bradley N. Miller and David ranum under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC-BY-NC-SA) License link: https://goo.gl/m2m1ww
Views: 2969 Gerry Jenkins
Timing python operations
 
00:57
This video is part of the Udacity course "Machine Learning for Trading". Watch the full course at https://www.udacity.com/course/ud501
Views: 4521 Udacity
12  Matplotlib Magic Function in Jupyter Notebook
 
02:14
Published on May 07 2018: In this video,we will learn about the magic functions in Jupyter notebook. We will be looking at the Matplotlib function. Please find below the code i have used in the example. %matplotlib inline import matplotlib.pyplot as plt plt.plot(range(30)) In the previous video, we learnt about keyboard shortcut/shortcuts for Jupyter Notebook. Previous Video: https://youtu.be/euFmFN-_8JU Additional Reading material: NA SUBSCRIBE to learn more about Power BI,Power Query, Power Pivot, Excel,SQL Server and Python!! https://www.youtube.com/channel/UCYYHFZpm5GbaOmQKDNSTGLw Our Playists: SQL Playlist :https://goo.gl/PS5Ep6 DAX PlayList : https://goo.gl/S4W41D Power BI PlayList: https://goo.gl/dXxvnB Power Query Playlist: https://goo.gl/5QS7P4 Getting Started with Power BI:https://goo.gl/GHakLZ Getting Started with Python: https://goo.gl/n24P3w Data Science With Python:https://goo.gl/PeYCR5 ABOUT DAGDOO: Website: Home Page: http://www.dagdoo.org/ Power BI Tutorials: http://www.dagdoo.org/excel-learning/tutorial-power-bi-desktop/ Questions? Comments and SUGESTIONS? You will find me here: Twitter: @dagdooe Category: Science & Technology License: Standard YouTube License
Views: 765 Learn 2 Excel
15  writefile Magic Function Jupyter Notebook
 
01:39
Published on May 15 2018: In this video, we will learn to write to a file using writefile magic function in jupyter notebook. In the previous video, we learnt about the time magic function in Jupyter Notebook Code used in the video: %%writefile C:\Data\data\test.txt Hello World!! Previous Video: https://youtu.be/W_-N33CG--A Additional Reading material: NA SUBSCRIBE to learn more about Power BI,Power Query, Power Pivot, Excel,SQL Server and Python!! https://www.youtube.com/channel/UCYYHFZpm5GbaOmQKDNSTGLw Our Playists: SQL Playlist :https://goo.gl/PS5Ep6 DAX PlayList : https://goo.gl/S4W41D Power BI PlayList: https://goo.gl/dXxvnB Power Query Playlist: https://goo.gl/5QS7P4 Getting Started with Power BI:https://goo.gl/GHakLZ Getting Started with Python: https://goo.gl/n24P3w Data Science With Python:https://goo.gl/PeYCR5 ABOUT DAGDOO: Website: Home Page: http://www.dagdoo.org/ Power BI Tutorials: http://www.dagdoo.org/excel-learning/tutorial-power-bi-desktop/ Questions? Comments and SUGESTIONS? You will find me here: Twitter: @dagdooe Category: Science & Technology License: Standard YouTube License
Views: 181 Learn 2 Excel
Calculating Cell Execution Time in Jupyter Notebook
 
03:12
This video explains how to calculate the cell execution time in jupyter notebook. More awesome topics covered here: Intermediate Python: http://bit.ly/2sdlEFs Functional Programming in Python: http://bit.ly/2FaEFB7 Python Package Publishing: http://bit.ly/2SCLkaj Multithreading in Python: http://bit.ly/2RzB1GD Multiprocessing in Python: http://bit.ly/2Fc9Xrp Parallel Programming in Python: http://bit.ly/2C4U81k Concurrent Programming in Python: http://bit.ly/2BYiREw Dataclasses in Python: http://bit.ly/2SDYQub Exploring YouTube Data API: http://bit.ly/2AvToSW Jupyter Notebook (Tips, Tricks and Hacks): http://bit.ly/2At7x3h Decorators in Python: http://bit.ly/2sdloX0 Inside Python: http://bit.ly/2Qr9gLG Exploring datetime: http://bit.ly/2VyGZGN Computer Vision for noobs: http://bit.ly/2RadooB Python for web: http://bit.ly/2SEZFmo Awesome Linux Terminal: http://bit.ly/2VwdTYH Tips, tricks, hacks and APIs: http://bit.ly/2Rajllx Optical Character Recognition: http://bit.ly/2LZ8IfL Facebook Messenger Bot Tutorial: http://bit.ly/2BYjON6 #python #jupyter #execution-time
Views: 185 Indian Pythonista
Python OOP - 5 , Magic Methods (dunder methods), ileri seviye Python programlama
 
23:50
Merhaba arkadaşlar bu dersimizde Python da nesne yönelimli programlama ile ilgili olarak Magic Methods ve Overloading kavramları ile ilgili alıştırmalar yapacağız. Pythonda Object-Oriented Programming derslerine Magic methods yani Dunder methods incelemesi ile devam edeceğiz ve __str__ , __repr__ , __add__ kavramlarını öğreneceğiz. Magic Methods ve Overloading kavramlarını öğrenecek olduğumuz dersimizde yine etkili ve öğrenmenizi kolaylaştıran python örnekleri üzerinde duracağız. Sende Paylaş Daha Çok Öğrenen Olsun Haydi Derse :) Anahtar Kelimeler, python magic methods, __str__ using, __add__ using, __repr__ using, __str__ ve __repr__ farkları, dunder methods python, python sihirli fonksiyonlar, python kalıtım, sınıf kalıtımı, python inheritances, python subclass, isintance, python @classmethod, python @statikmethod python sınıf methodları, python statik method kullanımı, python method kullanımı, nesne yönelimli python, oop python, python oop lessons, free python lessons, python class, ileri seviye python dersleri, nesne yönlümli python, python class variable, class variable python, python create class, pythons scope, python projects, simple python, __init__ kullanımı, pythonda nesne oluşturma, python args, python *args, python**kwargs, pythonda arguman kullanimi, regular expression python, python düzenli ifadeler, python fonksiyonlarda argüman kullanımı, how o use args with python, python reduce, reduce fonskiyonu, python ileri seviye programlama teknikleri, reduce fonksiyonu nedir, python filter(), filter() function, python da filter fonskiyonu, filter fonksiyonu nasıl kullanılır, map ve filter fonksiyonu, python map function, how use map function, map fonksiyonu kullanımı, python dersleri, python programlama dersleri, izmir python programlama, python lambda fonkisyonu, lambda fonkisyonu kullanımı, lambda fonksiyonu nasıl kullanılır, Pythonda oyun yapımı, Python GUI kullanımı, python map() fonction Her konuda farklı örnekleri bulabilecek olduğumuz dersimiz ile ilgili aklınıza takılan ve paylaşmak istediklerinizi yorum kısımlarında paylaşınız Kanalıma Abone Olmayı Unutmayın http://www.youtube.com/c/SinanUrun Örnek ile ilgili kodları github üzerinden aşağıdaki adresten edinilebilir https://github.com/sinanurun Yine Daha Detaylı bilgi almak adına Python Programlamanın Temelleri video Serimizi İnceleyebilirsiniz. https://www.youtube.com/playlist?list=PLv5gvG08kLQekD20hqte2ptaV-O_QKybV Farklı Örnekler için: http://sinanurun.com https://github.com/sinanurun/Python_ileri_seviye Udemy Üzerinden Ücretsiz Python Kursudan Faydalanmak İçin Aşağıdaki Bağlantıyı Takip Edebilirsiniz. https://www.udemy.com/python-programlamann-temelleri Öğrenmeyi Seven Öğretmenden Bir Ders Hikayesi Daha Dinlemeye Hazırsanız Haydi Derse :)
Views: 481 Sinan Urun
17  HTML magic Function Jupyter Notebook
 
02:01
Published on May 22 2018: In this video, we will learn to use the HTML magic function. We will import a file a .jpg file into jupyter notebook. In the previous video, we learnt how to find the filenames in a given directory. Code used in the video: Previous Video: https://youtu.be/bHmaRMO_Ei0 Additional Reading material: NA SUBSCRIBE to learn more about Power BI,Power Query, Power Pivot, Excel,SQL Server and Python!! https://www.youtube.com/channel/UCYYHFZpm5GbaOmQKDNSTGLw Our Playists: SQL Playlist :https://goo.gl/PS5Ep6 DAX PlayList : https://goo.gl/S4W41D Power BI PlayList: https://goo.gl/dXxvnB Power Query Playlist: https://goo.gl/5QS7P4 Getting Started with Power BI:https://goo.gl/GHakLZ Getting Started with Python: https://goo.gl/n24P3w Data Science With Python:https://goo.gl/PeYCR5 ABOUT DAGDOO: Website: Home Page: http://www.dagdoo.org/ Power BI Tutorials: http://www.dagdoo.org/excel-learning/tutorial-power-bi-desktop/ Questions? Comments and SUGESTIONS? You will find me here: Twitter: @dagdooe Category: Science & Technology License: Standard YouTube License
Views: 890 Learn 2 Excel
Analysis 6 | timeit 2
 
09:37
continue with python timeit, and about import vs from. These videos are to help you when reading the ebook: "Problem Solving with Algorithms and Data Structures using Python" at ebook: https://goo.gl/1GJCgt images of the ebook and some code from the book are attributed to this book by the Authors Bradley N. Miller and David ranum under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC-BY-NC-SA) License link: https://goo.gl/m2m1ww
Views: 879 Gerry Jenkins
Learn Jupyter Notebooks (pt.4) Using Interactive Widgets
 
18:58
In this video, we go through a simple example with Ipython widgets to interact with a Matplotlib plot. Github link to notebook: https://github.com/markjay4k/fourier-transform Ipython widgets docs: https://ipywidgets.readthedocs.io/en/latest/user_guide.html facebook group: https://www.facebook.com/MarkJay4k/?ref=aymt_homepage_panel
Views: 9514 Mark Jay
*args vs **kwargs | Advanced Python | Tutorial 15
 
15:09
Variable length arguments in Python are a great tool for playing with different ways to read arguments in your function. Here is a complete tutorial on using two different types of variable length arguments in Python. ================== Sections and Timeline ================== 1) *args - 0:45 2) **kwargs - 1:13 3) *args practice session - 2:15 4) **kwargs practice session - 5:42 5) Order of different types of arguments - 8:33 For practice, go ahead to - www.edabit.com/challenges
Views: 1007 PyLenin
16  Ls magic function jupyter notebook
 
01:42
Published on May 20 2018: In this video, we will learn how to find the filenames in a given directory. We will use the ls function for that. It is like the dir function if you come from a windows background. In the previous video, we learnt to write to a file using writefile magic function in jupyter notebook. Code used in the video: %ls Previous Video: https://youtu.be/mCEj1s4NWwE Additional Reading material: NA SUBSCRIBE to learn more about Power BI,Power Query, Power Pivot, Excel,SQL Server and Python!! https://www.youtube.com/channel/UCYYHFZpm5GbaOmQKDNSTGLw Our Playists: SQL Playlist :https://goo.gl/PS5Ep6 DAX PlayList : https://goo.gl/S4W41D Power BI PlayList: https://goo.gl/dXxvnB Power Query Playlist: https://goo.gl/5QS7P4 Getting Started with Power BI:https://goo.gl/GHakLZ Getting Started with Python: https://goo.gl/n24P3w Data Science With Python:https://goo.gl/PeYCR5 ABOUT DAGDOO: Website: Home Page: http://www.dagdoo.org/ Power BI Tutorials: http://www.dagdoo.org/excel-learning/tutorial-power-bi-desktop/ Questions? Comments and SUGESTIONS? You will find me here: Twitter: @dagdooe Category: Science & Technology License: Standard YouTube License
Views: 201 Learn 2 Excel
Ben Shaw: Python is slow, make it faster with C
 
19:52
= = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = Ben Shaw: Python is slow, make it faster with C = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = @ Kiwi PyCon 2014 - Saturday, 13 Sep 2014 - Track 2 http://kiwi.pycon.org/ **Audience level** Intermediate **Description** Most people have heard that it's possible to integrate Python with C to give performance boosts to computationally heavy code, but because it seems daunting they've never given it a try. It's actually not as hard as you think. This talk covers some of the different methods of speeding up your code with C, and compares the results to those you can get from other methods, like using PyPy. **Abstract** Introduction As developers, we like to work with Python because it's forgiving, quick to develop for and allows our code to be very dynamic. Unfortunately the trade-off for this magic is lower performance than compiled languages. Python can be sped up by offloading heavy algorithms to compiled C, using specially built C modules utilising the C Python API, or by integrating existing C libraries with using the python ctypes module. It is also possible to speed up Python using alternative interpreters, like PyPy, which uses a JIT compiler. Pure Python Implementation First we will take a look at a CPU bound algorithm written purely in Python, and see how it performs. The program reads data and prints results. The time it takes to run this will be considered the worst case scenario. Pure C Implementation The same program will be re-written in C, including the input and output logic, and we will compare the time it takes to run against the Python implementation. The results of the C implementation will be considered the best case scenario. Custom Python Module with C Implementation Python provides an API, C development headers and special C types, to allow the creation of a specially built bridges between Python and C code. In this example, the algorithm will be written in C, and bridged to Python with a custom Python/C module. Input and output takes place within Python, with C only performing the computation. With this method we can achieve near best-case speeds, at the cost of some additional (and sometimes complicated) C coding. Bridging To C with ctypes Introduced in Python 2.5, ctypes allows Python to integrate with pre-built C libraries without custom C code. This approach has the advantage over the custom Python/C Module of not needing to write a lot of boilerplate and bridging code in C. As with the Py/C implementation, C is used only to execute the algorithm, and Python takes care of input and output. Again, performance is close to best-case speeds, but the work to integrate with C is much less. Alternative Python Implementations PyPy uses a JIT compiler to offer impressive performance gains. The original Python code will be run through PyPy, and although the results might not be as quite as good as using compiled C, they come close, and the effort-to-gain ratio certainly makes it attractive option. Conclusion Each performance boosting option has its pros and cons, and when it's so easy to just use PyPy and get good results, why would you still use C? We'll look at some example use cases for each of the methods presented and why you would choose one over the others. **Slides** https://speakerdeck.com/nzpug/ben-shaw-python-is-slow-make-it-faster-with-c
4. NumPy Basics - IPython Notebook Tutorial
 
30:43
NumPy tutorial using IPython Notebook development environment. We compare performance of ndarray vs python list performance and basic mathematical operations. We cover most common functions and indexing & slicing. IPython magic used is %timeit, %%timeit and %%capture. We covered the most common functions of NumPy which are: **List Creation** - np.arange() - np.array() - np.zeros() - np.random.random() - np.linspace() **Statistical analysis** - np,max() - np.min() - np.mean() - np.median() - np.std() **Reshaping** - np.reshape() - np.ravel() This is open source, Github/NBViwer: http://nbviewer.ipython.org/github/twistedhardware/mltutorial/blob/master/notebooks/IPython-Tutorial/4%20-%20Numpy%20Basics.ipynb
Views: 49375 Roshan
3. Basic Python - IPython Notebook Tutorial - bad video
 
10:05
This tutorial covers working with code cells and IPython magic and getting help about your objects using object? , object?? and help(object). Other IPython magic codes in this tutorial are: %quickref, %lsmagic %timeit and %%timeit. Finally, we cover In[] and Out[] lists and the underscore for accessing the last output. This is open source, Github/NBViwer: http://nbviewer.ipython.org/github/twistedhardware/mltutorial/blob/master/notebooks/IPython-Tutorial/3%20-%20Basic%20Python.ipynb
Views: 15 Roshan
Learn Jupyter Notebooks (Pt.3) Animated Plotting
 
22:53
In this video we will do an in depth example of animated plotting in Jupyter Notebooks. Github: https://github.com/markjay4k/fourier-transform Facebook page: https://www.facebook.com/MarkJay4k/
Views: 9745 Mark Jay
ssh ipython notebook magic
 
00:30
ssh into a remote machine and start jupyter (ipython) notebook. With ssh tunneling and an iterm2 trigger, you can get it to automatically open a local browser connected to the remote notebook! 3-step instructions available here: https://duetosymmetry.com/code/ssh-ipython-notebook-magic/
Views: 616 Leo Stein
Building Interactive Applications and Dashboards in the Jupyter Notebook
 
39:26
Romain Menegaux (Bloomberg LP), Chakri Cherukuri (Bloomberg LP) demonstrate how to develop advanced applications and dashboards using open source projects, illustrated with examples in machine learning, finance, and neuroscience. Subscribe to O'Reilly on YouTube: http://goo.gl/n3QSYi Follow O'Reilly on: Twitter: http://twitter.com/oreillymedia Facebook: http://facebook.com/OReilly Instagram: https://www.instagram.com/oreillymedia LinkedIn: https://www.linkedin.com/company-beta/8459/
Views: 39163 O'Reilly
Plotly Web Based Visualization - Basic Charts Using Python Pandas- Tutorial 36 in Jupyter Notebook
 
19:47
In this Python for Data Science Tutorial, You will learn about Web Based Data Visualization using Plotly in Python. Plotly is used to make interactive graphs and MapsThe environment used is Jupyter notebook of Anaconda. You will learn about how to create Line charts, bar charts and Pie charts with the help of Plotly in Python. This is the 36th Video of Python for Data Science Course! In This series I will explain to you Python and Data Science all the time! It is a deep rooted fact, Python is the best programming language for data analysis because of its libraries for manipulating, storing, and gaining understanding from data. Watch this video to learn about the language that make Python the data science powerhouse. Jupyter Notebooks have become very popular in the last few years, and for good reason. They allow you to create and share documents that contain live code, equations, visualizations and markdown text. This can all be run from directly in the browser. It is an essential tool to learn if you are getting started in Data Science, but will also have tons of benefits outside of that field. Harvard Business Review named data scientist "the sexiest job of the 21st century." Python pandas is a commonly-used tool in the industry to easily and professionally clean, analyze, and visualize data of varying sizes and types. We'll learn how to use pandas, Scipy, Sci-kit learn and matplotlib tools to extract meaningful insights and recommendations from real-world datasets. Download Link for Cars Data Set: https://www.4shared.com/s/fWRwKoPDaei Download Link for Enrollment Forecast: https://www.4shared.com/s/fz7QqHUivca Download Link for Iris Data Set: https://www.4shared.com/s/f2LIihSMUei https://www.4shared.com/s/fpnGCDSl0ei Download Link for Snow Inventory: https://www.4shared.com/s/fjUlUogqqei Download Link for Super Store Sales: https://www.4shared.com/s/f58VakVuFca Download Link for States: https://www.4shared.com/s/fvepo3gOAei Download Link for Spam-base Data Base: https://www.4shared.com/s/fq6ImfShUca Download Link for Parsed Data: https://www.4shared.com/s/fFVxFjzm_ca Download Link for HTML File: https://www.4shared.com/s/ftPVgKp2Lca
Views: 8871 TheEngineeringWorld
Magic Numbers
 
07:28
Views: 2865 CS50
Learn Python : 08 : Classes and Objects
 
12:10
This python tutorial lesson is part of a series on programming in python. This is Part 8 covering Classes and Objects. Git hub with all Jupyter Notebooks in .pynb format are here: https://github.com/frankcarmody/learnPython This video uses a Jupyter notebook, imported into https://my.datascientistworkbench.com Notebook: https://raw.githubusercontent.com/frankcarmody/learnPython/master/learnPython.08.ClassesAndObjects.ipynb
Views: 706 Education Public
Learn Python : 07 : Functions
 
10:05
This python tutorial lesson is part of a series on programming in python. This is Part 7 covering Functions. Git hub with all Jupyter Notebooks in .pynb format are here: https://github.com/frankcarmody/learnPython This video uses a Jupyter notebook, imported into https://my.datascientistworkbench.com Notebook: https://raw.githubusercontent.com/frankcarmody/learnPython/master/learnPython.07.Functions.ipynb
Views: 741 Education Public
A multithreaded blinking theremin powered by ZERYNTH
 
00:47
www.zerynth.com Check out how to develop a simplified theremin-like instrument that changes the pitch played as you wave your hand over an Infrared Proximity Sensor. In addition you can easily vary the length of the "beat" and drive various blinking LEDs (seemingly) all at the same time... it's the magic of multi-threading! Despite its apparent complexity, this project requires very simple electronics, as most of the dirty jobs is done for you by ZERYNTH! ZERYNTH is a multi-board compatible IoT development suite for makers, designers and IoT developers. ZERYNTH supports rapid product development and integration with sensors and cloud services, reducing development time and efforts. Find out more about this project on Hackster https://www.hackster.io/5841/a-multithreaded-blinking-theremin-powered-by-viper-c61921?ref=platform&ref_id=5378_trending___&offset=8
Views: 1191 Zerynth
Learn Jupyter Notebooks (Pt. 1) Plotting
 
13:51
In this video, I give a quick into to Jupyter Notebooks and show you how to plot and use LaTeX markdown.
Views: 22557 Mark Jay
Magic Snake Cake Mold
 
01:00
Get it here: bit.ly/2gSgusG kitchengadgetfreaks.com If you want to bake a cake in all shapes without you waste the time, This Magic Snake Cake Mold is the best choice for making cakes. Baking mold snakes are easy for making cakes in many different shapes, and should not miss from your kitchen. Silicone Cake Molds are easy to use and flexible, non-stick, durable and dishwasher safe. Bake your cake in any shapes you want, simply you connect the Snake Cake Mold together to form different shape you like, then pour batter in your cake mix and put it in oven. In addition, it can be used in all gas and electric ovens. This Magic Snake Cake Mold is a great utensil for anyone who wants to make cake all kinds of shapes without take a lot of time, it also save your money and it super easy to clean and store. Save time, save money, bake easy, and DIY different cake shapes.
Folder Management - IPython Notebook Tips
 
02:03
With the new folders in IPython notebook you can organize your notebooks into folder. Create and manage folders from with in IPython Notebook interface using %%bash cell magic.
Views: 3415 Roshan
DataAnalysis with Python pandas - Introduction to cell types and cell mode in Jupyter - 6
 
05:01
Visit complete course on Data Science with Python : https://www.udemy.com/data-science-with-python-and-pandas/?couponCode=YTSOCIAL090
Views: 262 MyStudy
Learn Jupyter Notebooks (pt.1a) Hydrogen with Atom
 
02:16
In this video I show a plugin called Hydrogen, which adds Jupyter like functionality to Atom.
Views: 12979 Mark Jay
PLOTCON 2017: Chris Holdgraf, Visualizing the human brain
 
31:52
Brains are beautiful, complicated, and really hard to study. From the early days of single-cell imaging with microscopes, to the modern era studying activity across the entire brain simultaneously, visualizing the brain has always proven both fascinating and challenging. As data science begins to make its way into the world of neuroscience, open source tools are empowering neuroscientists to munge, analyze, and visualize data recorded from the most complicated organ on the planet. This talk focuses on visualizing the human brain, with a focus on how we got here, and where we’re going next. Biography Chris is a graduate student in Bob Knight’s cognitive neuroscience laboratory. He uses applied statistics and machine learning to study the brain, utilizing encoding and decoding models of electrophysiology signals to study how our experience with the auditory world affects the way that we process sounds. He’s a regular contributor to the MNE-python project for MEG and EEG data analysis in Python and to a handful of tools in the scientific python ecosystem. Chris believes strongly in the importance of teaching, communicating science, and connecting with the non-academic world. He’s interested in the practice of teaching data analysis, statistics, and programming to scientists and is exploring ways to improve these practices in undergraduate and graduate education. He’s involved in the Berkeley Data Science Education Program, assisting faculty in preparing courses for the Data 8 undergraduate course in data science. When he’s not coding, writing, collecting data, or in a meeting, he tries to spend as much time as he can going for hikes, playing basketball, traveling, and eating barbecue.
Views: 575 Plotly
Data Analysis with Pandas and Python - 01 13 - Code Cell Execution
 
04:48
Get the complete 19+ hour Udemy course here: https://www.udemy.com/data-analysis-with-pandas/?couponCode=FIFTEEN
Views: 208 BP Solutions
Ipython/Jupyter notebook - Split Cell Tutorial.
 
03:13
Demo of split cells in the ipython/jupyter notebook. Code is Currently here. https://github.com/cdknorow/notebook.git My Gitlab https://gitlab.com/u/cknorow My LiveStream https://www.livecoding.tv/simpleliqui... Just a friendly data scientist,
Views: 3464 Chris Knorowski
Revolver Timing Issues - Fitting the Bolt
 
15:37
Sometimes revolvers have issues regarding the fitting of the bolt to the cylinder. The peening of the cylinder as the bolt comes down too early and putting an ugly dent into the notch is a common problem with many of the Uberti and Pietta percussion cap revolvers. Careful modifications can remedy the situation but each revolver is different and must be approached as such. Don't forget to buy extra hammers as you will destroy some if it's your first time. It's not voodoo or black magic, just some careful modifications. ****BE ALERT, WORKING ON YOUR FIREARMS CAN BE DANGEROUS, WE CANNOT BE RESPONSIBLE FOR ANY ERRORS ON YOUR PART. SEEK OUT SOMEONE COMPETENT IF YOU DON'T FEEL CONFIDENT IN YOUR ABILITIES***
Views: 46299 mannyCA
Progress Bar in Jupyter Notebook
 
02:01
This video explains how to create progress bars in jupyter notebook. More awesome topics covered here: Intermediate Python: http://bit.ly/2sdlEFs Functional Programming in Python: http://bit.ly/2FaEFB7 Python Package Publishing: http://bit.ly/2SCLkaj Multithreading in Python: http://bit.ly/2RzB1GD Multiprocessing in Python: http://bit.ly/2Fc9Xrp Parallel Programming in Python: http://bit.ly/2C4U81k Concurrent Programming in Python: http://bit.ly/2BYiREw Dataclasses in Python: http://bit.ly/2SDYQub Exploring YouTube Data API: http://bit.ly/2AvToSW Jupyter Notebook (Tips, Tricks and Hacks): http://bit.ly/2At7x3h Decorators in Python: http://bit.ly/2sdloX0 Inside Python: http://bit.ly/2Qr9gLG Exploring datetime: http://bit.ly/2VyGZGN Computer Vision for noobs: http://bit.ly/2RadooB Python for web: http://bit.ly/2SEZFmo Awesome Linux Terminal: http://bit.ly/2VwdTYH Tips, tricks, hacks and APIs: http://bit.ly/2Rajllx Optical Character Recognition: http://bit.ly/2LZ8IfL Facebook Messenger Bot Tutorial: http://bit.ly/2BYjON6 #python #jupyter #tqdm
Views: 318 Indian Pythonista

60 gracefield road artane dublin
Paroxetine hcl cr 12 5mg oxycontin
Zocor 20 mg desire
What is prinivil 20 mg
70 avowed socialists in u.s. congress