#python

Histogram Equalization in #python from Scratch
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Histogram Equalization is one of the fundamental tools in the image processing toolkit. It’s a technique for adjusting the pixel values in an image to enhance the contrast by making those intensities more equal across the board. Typically, the histogram of an image will have something close to a normal distribution, but equalization aims for a uniform distribution. In this article, we’re going to program a histogram equalizer in python from scratch. If you want to see the full code, I’ve included a link to a Jupyter notebook at the bottom of this article. Now, if you’re ready, let’s dive in!Before anything, we have to do some setup. Let’s import the libraries we’ll be using throughout the program, load in the image, and display (...)

#image-processing #computer-vision #hackernoon-top-story #development

10 Great Articles On Data Science And #programming!
▻https://hackernoon.com/10-great-articles-on-data-science-and-programming-eec816941896?source=rs

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Data science and programming are two topics that continue to expand and evolve as computation, knowledge bases and best practices continue to improve. This makes it very difficult to keep up with all the new articles and bodies of thought. So We compiled a list of 10 articles we or other people have enjoyed in the past year or so on the topics of programming, data science and machine learning. We hope they provide you new perspective as well as practical advice.1. Why businesses fail at machine learningby Cassie KozyrkovImagine hiring a chef to build you an oven or an electrical engineer to bake bread for you. When it comes to machine learning, that’s the kind of mistake I see businesses making over and over.If you’re opening a bakery, it’s a great idea to hire an experienced baker (...)

#analytics #data-science #self-improvement #python

Bien configurer ses #Tests #Python avec tox et Travis
▻https://makina-corpus.com/blog/metier/2019/bien-configurer-ses-tests-python-avec-tox-et-travis

Le plus difficile dans le développement des tests unitaires c’est souvent de se motiver à écrire les premières lignes... Alors qu’une fois que c’est initié, ça devient très simple d’en ajouter. Nous verrons dans cet article de blog comment le faire rapidement avec tox et Travis !

#News_Item

i-1000th idea to make money online via #python-chained sqlmaps!
▻https://hackernoon.com/i-1000th-idea-to-make-money-online-via-python-chained-sqlmaps-c8793a6897

My i-1000th idea to make money online came to me one morning when playing around with Kali tools and gaining access to stuff I shouldn’t have access to. There was a little bit of a moral dilemma that came to play when I thought to myself about the opportunity to see if someone’s password was re-used on other sites when I found 10s 1000s of them in plain text, or create a mailing list to sell like merchandise from lists of 10s 1000s emails on different sites online… but I thought I’d take the whitehat approach and see if I could make people aware of some of their security holes in exchange for the opportunity to sell them security solutions.#1) Create a #pentesting automated script that identifies open databases or other security holesThere’s myriad tools that come to mind to make this (...)

#hacking #penetration-testing #development

Commit, push, deploy — #git in the Microsoft #azure #cloud
▻https://hackernoon.com/commit-push-deploy-git-in-the-microsoft-azure-cloud-403fb135bcf4?source=

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Commit, push, deploy — Git in the Microsoft Azure CloudFollow me on Twitter, happy to take your suggestions on topics or improvements /ChrisWe have come to rely on Git as our default version control tool ever since it was released, it has become de facto standard even if other options exist. Git helps us manage our source code, divide it in branches and it even helps us working with other developers on places like for example GitHub or GitLab by allowing us to create Pull/Merge requests. Wouldn’t it be great if Git can be there for us when we move our Apps to the Cloud?This article will cover the following:Download a sample app, we want to focus on understanding #deployment with Git so we will take some ready-made codeRun the app locally just to ensure it works, this is a must, if it works (...)

#python

Taking Data Visualization to Another Level
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Courtesy: ▻https://pixabay.com/illustrations/background-data-network-web-3228704/When you tend to use one library for a certain period of time, you get used to it. But, you need to evolve and learn something new every day. If you are still stuck up with Matplotlib(Which is amazing), Seaborn(This is amazing too), Pandas(Basic, yet easy Visualization) and Bokeh, You need to move on and try something new. Many amazing visualization libraries are available in #python, which turns to be very versatile. Here, I’m going to discuss about these amazing libraries:PlotlyCufflinksFoliumAltair + VegaD3.js (My best Pick, i code in JS too)If you are aware and use the libraries mentioned above then you are on the right track of evolution. They can help in generating some amazing visualizations and syntax (...)

#javascript #data-visualization #data-analysis #data-science

Linear Programming in #python : A Straight Forward #tutorial
▻https://hackernoon.com/linear-programming-in-python-a-straight-forward-tutorial-a0d152618121?so

Linear programming is one of the most common #optimization techniques. It has a wide range of applications and is frequently used in operations research, industrial design, planning, and the list goes on. Alas, it is not as hyped as machine learning is (which is certainly a form of optimization itself), but is the go-to method for problems that can be formulated through decision variables that have linear relationships. This is a fast practical tutorial, I will perhaps cover the Simplex algorithm and the theory in a later post.Problem StatementJust to get an idea, we are going to solve a simple problem regarding production scheduling. Imagine that you work for a company that builds computers. A computer is a fairly complex product, and there are several factories that assemble them (...)

#mathematics #machine-learning

3 #programming Languages to Learn in 2019
▻https://hackernoon.com/3-programming-languages-to-learn-in-2019-2eb035936f65?source=rss----3a81

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Disclaimer: This is completely my personal opinion and derived from my personal experiences. Feel free to share any thoughts.I still remember in 2013, I started learning my first programming language in C++, wrote my first “Hello World”, and was excited like a little kid. Now that I have been programming professionally and fortunate enough to work with many different technologies, I have gathered some thoughts on my personal top 5 languages that people should learn in 2019. So, if you are new to the coding world, I recommend these languages.With that said, let’s get right into the first programming language on my list:PythonMany developers love #python and I’m sure most professional programmers have done some coding in Python at least once in his/her career. According to the stats provided (...)

#programming-languages #go #javascript

Atelier python au Blenderlab Fablab : Ce mercredi soir de 19h à 21h au blenderlab, on code son site web en #python. #codingisfun #codeismylife #learntocode #flask #diy…
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Ce mercredi soir de 19h à 21h au @blenderlab, on code son site web en #python. #codingisfun #codeismylife #learntocode #flask #diy #apprendreacoder #Lille ▻https://www.blenderlab.fr/evenement/atelier-coding-cours-du-soir-2019-03-06

Finding High-impact Performance Bottlenecks — #django Tips
▻https://hackernoon.com/finding-high-impact-performance-bottlenecks-django-tips-237a896e0f91?sou

Finding High-impact Performance Bottlenecks In DjangoPhoto from Pexels.comHow to find bottlenecks in Django which have a high impact on the application performance.Originally published at ▻https://avilpage.com/2018/12/django-bottleneck-performance-scaling.htmlIntroductionWhen optimizing the performance of web application, a common mistake is to start with optimizing the slowest page(or API). In addition to considering response time, we should also consider the traffic it is receiving to prioritize the order of optimization.In this article, we will profile a Django web app, find high-impact performance bottlenecks and then start optimizing them to yield better performance.Profilingdjango-silk is an open source profiling tool which intercepts and stores HTTP requests data. Install it with (...)

#python #apm #django-tricks #django-tips

If you can see it, you can scrape it!
▻https://hackernoon.com/if-you-can-see-it-you-can-scrape-it-1f51561933d9?source=rss----3a8144eab

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A set of six steps that can help you scrape a website and generate candlestick charts.Yes! Anything that you see on any website can be scraped. From searching a house for rent to analyzing stocks, web scraping make things easy. You can extract data as and when you wish and use it for your need.In this blog I will walk you through the six steps that I followed to scrape the website of National Stock Exchange and analyze the data using candlestick charts. Let’s get started with some definition now.What is web scraping?Web scraping or web harvesting is a technique used to extract data such as weather reports, market pricing or any data that you wish, from different websites across the web.I find using APIs simple, compared to using web scraping. If you can find an API well and good, there (...)

#web-scraping #web-scraping-tools #data-extraction #python #candlestick-charts

A Guide to Building a Multi-featured #slackbot with #python
▻https://hackernoon.com/a-guide-to-building-a-multi-featured-slackbot-with-python-73ea5394acc?so

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Chatbots are being used almost everywhere today from social messaging platforms to integration into websites for booking tickets, finding nearby restaurants, generating leads, buying and selling products. Some #chatbots, like Ruuh by Microsoft have been able to deliver human-like conversations using artificial intelligence and deep learning.Do you remember Natasha from Hike? I used it 4 years ago and was amazed to see how she handled our conversations which were so much better than a bot could possibly handle. I hadn’t heard the concept of machine learning back then.Now chatbots have made us so dependent on them that it has become a part of our lives today.“Ok Google, remind me on 20th to publish my chatbot article”“What time?”“Midnight”“Sure, I’ll remind you on Wednesday at midnight.”Chatbots (...)

#machine-learning #web-development

What You Didn’t Know About Crypto Hedge Funds - Part 1
▻https://hackernoon.com/what-you-didnt-know-about-crypto-hedge-funds-part-1-209b9d9215a7?source=

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What You Didn’t Know About Crypto Index Funds — Part 1Or maybe you already knew this. Then… ¯\(ツ)/¯In the last couple of years, a lot of crypto ‘hedge’ funds have appeared. In this series I’ll analyze how a lot of them would have performed VS #bitcoin, with data from 2013 until June 2018 scraped from Coinmarketcap.‘Hedge’ funds?Well, originally the hedge in a hedge fund meant that risks were limited by having short positions in addition to the long ones, making the fund market neutral. This is not a common thing in these crypto funds, where they’re mostly long.So what?In this series I’ll analyze a particular type of fund where almost all of the data is publicly available: index funds. I will recreate the return on investment of #investing into crypto index funds across the past 5 years (even when (...)

#hedge-funds #python #index-funds

Using a multivariable linear regression model to predict the sprint speed of players in FIFA 19
▻https://hackernoon.com/using-a-multivariable-linear-regression-model-to-predict-the-sprint-spee

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Using a multivariate linear regression model to predict the sprint speed of players in FIFA 19FIFA 19 Source: Express.co.ukI play FIFA games occasionally but classify myself as a relatively strong player who wins more often than not against other casual players. I am not a huge soccer fan in general and do not try and play a strategic game. Instead I rely heavily on player sprint speed and making unpredictable runs and turns. I often combine these skills to find and make spaces in my opponents space and dribble my way to a victory - much to the frustration of my opponent. Given this backdrop, I decided to download the FIFA19 dataset from Kaggle with the intention of predicting player sprint speed based on variables/features that I believed would best predict a player’s sprint (...)

#python #algorithms #machine-learning #data-science #linear-regression

Building a Neural Network Only Using NumPy
▻https://hackernoon.com/building-a-neural-network-only-using-numpy-7ba75da60ec0?source=rss----3a

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Using Andrew Ng’s Project Structure to Build a Neural Net in PythonIntroductionAfter having completed the deeplearning.ai Deep Learning specialization taught by Andrew Ng, I have decided to work through some of the assignments of the specialization and try to figure out the code myself without only filling in certain parts of it. Doing so, I want to deepen my understanding of neural networks and help others gain intuition by documenting my progress in articles. The complete notebook is available here.In this article, I’m going to build a neural network in #python only using NumPy based on the project structure proposed in the deeplearning.ai Deep Learning specialization:Define the structure of the neural network2. Initialize the parameters of the neural network defined in step one3. Loop (...)

#deep-learning #machine-learning #artificial-intelligence #data-science

Learn Pandas Via Usecases — Part 2
▻https://hackernoon.com/learn-pandas-via-usecases-part-2-e1503892191b?source=rss----3a8144eabfe3

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Learn #python Pandas Via Usecases — Part 2Use cases open up more functionalitiesIn the last blog, I hope I have sold you the idea that Pandas is an amazing library for quick and easy data analysis and it’s much easier to use than you thought. If you have not read my first blog about Pandas, please go through it before you move forward.Oops !! We missed Some DataIn the last blog, we saw basic Dataframe operations using sample sales data. Let’s assume you are a manager leading a sales team, and you were all happy about the sales trajectory and the pivot representation of the data you learned to create from our last blog.import numpy as npdf.pivot_table(index=["Country"], columns=["Region"], values=["Quantity"], (...)

#learning #data-science #statistics #machine-lear

Meet the tool that automatically infers #security vulnerabilities in #python code
▻https://hackernoon.com/meet-the-tool-that-automatically-infers-security-vulnerabilities-in-pyth

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TL;DRIn January 2019 we released a tool that significantly raises the bar for detecting security vulnerabilities in Python code. We built a fully automated system that couples data flow analysis algorithms with a novel ML component and detects many more new security issues than traditional approaches. After running it on several Open Source repositories, we found and reported 35 critical security vulnerabilities from the OWASP Top Ten list. Here’s a motivating screenshot that shows one of them:One of the XSS vulnerabilities that we found and reportedThe interest towards Information Security and, in particular Web Applications security, is steadily growing over the past years. Unfortunately so does the threat level posed by security vulnerabilities that are silently awaiting to be (...)

#code-review #security-vulnerabilities #python-security

10 Popular Websites Built With #django Framework
▻https://hackernoon.com/10-popular-websites-built-with-django-framework-d0116ad3117d?source=rss-

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What is the frameworkRegardless of the sphere you work in, one of your most important tasks is to create a fast, good-looking website. Today, almost every business needs a website, which acts as a sort of business card for a company or online service. It helps you engage with customers, promote your business, increase sales and so on. In every case, the website should be fast, scalable and dynamic.When creating a website, you typically need to work with roughly the same set of basic components: ways to manage user authorizations (account creation, login); a user dashboard; file downloading and uploading, etc. If the tasks are the same, why not make them easier, and thereby reduce the cost of development? With this in mind, web frameworks appeared on the scene as a set of components (...)

#web-development #django-framework #websites-for-startups #python

#python #bootcamp For ML
▻https://hackernoon.com/python-bootcamp-for-ml-c321177b957e?source=rss----3a8144eabfe3---4

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A simple effort from me to make a Python bootcamp 3 Days for beginners who are enthusiastic about Machine Learning.Introduction:Few days ago i think that i can make a bootcamp on python which most needed for machine learning enthusiastic or deep learning enthusiastic or data science enthusiastic.Then i was started this bootcamp. I hope that this bootcamp will be helpful for everyone who’s want to work in Data Science field or Machine learning field.Data Science.AI CommunityLet’s start learning with us!!Photo on UnsplashPython Basic(Day-01)Data Science.AI CommunityWe are going to get familiar with Python. In Day-01 we was covered the basic portion of Python which can be very useful for Machine Learning or Data Science.What is python?Python is developed by Guido van Rossum. Guido van Rossum (...)

#hackernoon-top-story #data-science #machine-learning

#python and #finance: How to Level Up Your Spreadsheets
▻https://hackernoon.com/python-and-finance-how-to-level-up-your-spreadsheets-176682508370?source

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Source: Toptal“For professions that have long relied on trawling through spreadsheets, Python is especially valuable. Citigroup, an American bank, has introduced a crash course in Python for its trainee analysts.” — The EconomistFinance professionals have long had access to VBA (Visual Basic for Applications) in #excel to build custom functionality and automate workflows. With the emergence in recent years of Google Sheets as a serious contender in the spreadsheet space, Google Apps Script now offers an additional choice.However, I would like to draw attention to a third option, the Python programming language, which has become tremendously popular in a number of fields.In this article, I will provide some examples of what you can accomplish with Python, starting with an overview of the (...)

#data-science #python-spreadsheet

Socket Programming in #python : Client, Server, and Peer Examples
▻https://hackernoon.com/socket-programming-in-python-client-server-and-peer-examples-a25c9782b58

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Sockets (aka socket programming) enable programs to send and receive data, bi-directionally, at any given moment. This tutorial walks through how you can send data from device-to-device, client-to-server, and vice versa using socket programming in Python.▻https://medium.com/media/86144cd4f9efcf87701793197783133c/hrefWhy use #sockets to send data?Internet-connected applications that need to operate in realtime greatly benefit from the implementation of sockets in their networking code. Some examples of apps that use socket programming are:Web pages that show live notifications (Facebook, Twitch, eBay)Multiplayer online games (League of Legends, WoW, Counter Strike)Chat Apps (WhatsApp, WeChat, Slack)Realtime Data Dashboards (Robinhood, Coinbase)IoT devices (Nest, August Locks)Python, unlike (...)

#peer-to-peer #pubnub #socket-programming

Top Seven Apps Built With #python
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Over its almost 30 years of existence, Python has become one of the most popular programming languages. But if most startups once used it because of its simplicity and low cost, modern giants like Instagram or Spotify use Python and the Django framework to create smooth working experiences. Famously, Django provides fast work processes, clean design, and transparent functionality, among many other advantages. It allows developers at all levels to focus on writing their apps instead of reinventing the wheel (or fixing it, for that matter). On top of that, it’s free, open source, and has gathered a mighty community of developers over the years. Large companies appreciate this. To give you an example, let’s take a look at some apps written in Python that you probably didn’t know about.1. (...)

#python-app #most-used-python-apps #largest-python-apps #most-popular-python-apps

Understanding binary #search
▻https://hackernoon.com/understanding-binary-search-e82d7bcbc06f?source=rss----3a8144eabfe3---4

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Suppose, numbers is a list/array of integers that are sorted in nondecreasing order. We need to determine whether an element x is present in the list or not. There are n elements in the list .Linear searchBefore using binary search let’s check how linear search will perform in this problem.Let’s, n = 10⁶ ( here,numbers is a list of 10⁶ integers).If x is present at the first position of the list then we will get our expected result at the first iteration. This will work in O(1) time. Pretty fast! NO?But if x is present at 10⁶th position(or not present in the list) then it will take O(n) time to calculate the result and if we search for n times then time complexity will be O(n²), pretty slow, NO?So we can say that, at worst case linear search will work in O(n²) time complexity (for n number of (...)

#javascript #algorithms #binary-search #python

Building #python Data Science Container using #docker
▻https://hackernoon.com/building-python-data-science-container-using-docker-c8e346295669?source=

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Photo by Bryan Goff on UnsplashTL;DRArtificial Intelligence(AI) and Machine Learning(ML) are literally on fire these days. Powering a wide spectrum of use-cases ranging from self-driving cars to drug discovery and to God knows what. AI and ML have a bright and thriving future ahead of them.On the other hand, Docker revolutionized the computing world through the introduction of ephemeral lightweight containers. Containers basically package all the software required to run inside an image(a bunch of read-only layers) with a COW(Copy On Write) layer to persist the data.Enough talk let’s get started with building a Python data science container.Python Data Science PackagesOur Python data science container makes use of the following super cool python packages:NumPy: NumPy or Numeric Python (...)

#data-science-container #data-science #python-data-science

Cartographier le manteau neigeux avec #Python
▻https://makina-corpus.com/blog/metier/2019/python-carto

En quelques lignes de code, nous vous proposons de cartographier le manteau neigeux. Nous utiliserons pour cela les données du réseau nivo-météorologique français, ainsi que les bibliothèques Pandas et Folium.

#Cartographie #Dataviz #News_Item