#python

Recursion vs. Looping in #python
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One of the most fundamental tools in programming is a loop. While there are many different types of loops, almost each type of loop has the same basic function: iterating over data to analyze or manipulate it. Recursion is another popular type of function and although it can also analyze and manipulate sequences of data similar to a loop, recursion is probably less understood in many cases, and can often be somewhat confusing. Almost all recursive functions can be re-written as loops, and vice versa. However, each type of function has advantages and disadvantages, and knowing when to use one over the other is something we’ll take a look at here. In the following post, we’re going to try and answer the following questions:What is a For Loop?What is recursion?What is a practical example of (...)

#recursion-python #looping-python #hackernoon-top-story #javascript

A realistic roadmap to becoming a #python developer
▻https://hackernoon.com/a-realistic-roadmap-to-becoming-a-python-developer-ab5872959509?source=r

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This is a highly opinionated, pseudo-motivational, unconventional and almost rant-like developer roadmap article.This article is more than a compilation of best books/videos/courses to learn Python and covers the bigger issues that a beginner/early-intermediate faces on their journey. These are the undocumented problems Stack Overflow does not solve.Why Python ?Why should you learn Python anyway? Why not one of the 20 other languages trending right now? As you’re beginning your journey, this questions crops up multiple times (a day).Picking your first #programming language is a lot like picking a starter pokemon.The inherent capabilities of a language are less significant than the skill of the programmer in using said language and their grit to make it into the big league.If you want to (...)

#software-development #technology #computer-science

Are your #python programs running slow? Here’s how you can make them 7x faster.
▻https://hackernoon.com/are-your-python-programs-running-slow-heres-how-you-can-make-them-7x-fas

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We all know that Python is much slower than statically-typed #programming languages like C, C++, Java and some dynamic languages too like JavaScript and PHP. Let’s look at the reasons why Python is much slower compared to these languages and what can we do to increase its execution speed.Why is Python slow?The default implementation of Python ‘CPython’ uses GIL (Global Interpreter Lock) to execute exactly one thread at the same time, even if run on a multi-core processor as GIL works only on one core regardless of the number of cores present in the machine. Each core in the CPU has its own GIL, so a quad-core CPU will have 4 GILs running separately with its own interpreter. To make our python programs run parallel we use multithreading and multiprocessing.Multithreading does not make much (...)

#pypy #python-speed #python-programs

Text Generation for Char LSTM models
▻https://hackernoon.com/text-generation-for-char-lstm-models-685dc186e319?source=rss----3a8144ea

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Train a character-level language model on a corpus of jokes.I decided to experiment with approaches to this problem, which I found on #openai’s Request for Research blog. You can have a look at the code here. This is written in Pytorch, and is heavily inspired by Fast.ai’s fantastic lesson on implementing RNN’s from scratch.Data preparation I started off using the dataset provided by OpenAI. The data was converted to lowercase and for an initial run, I selected the top rated jokes, with a word length of less than 200. Here’s an example of all the tokens encountered:Explicit words ahead! This particular dataset has explicit words/content, so those come up in the output predictions of the model. Another interesting problem to work on would be to filter out inappropriate words from the output (...)

#programming #machine-learning #artificial-intelligence #python

#python v/s #php : Which #programming Language to Choose in 2019 ?
▻https://hackernoon.com/python-v-s-php-which-programming-language-to-choose-in-2019-45a95249ad8d

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In today’s disruptive tech world, Python and PHP are the two most-popular server-side languages in use. In many aspects, Python and PHP closely compete with each other because of its almost identical features. Their open-source benefits and productive features attract a majority of the businesses and developers to choose Python or PHP for app development.However, the battle to identify the best programming language is a never-ending sequel. In this blog, let’s address some of the prominent differences between Python and PHP and find out the best programming language to choose in 2019.A Brief History of PythonDeveloped by Guido van Rossum, Python is a general-purpose high-level programming language which was introduced in the year 1990. Due to its simplicity and ease of development, Python (...)

#php-vs-python

#python: list de-duping, list of lists batches
▻https://hackernoon.com/python-list-de-duping-list-of-lists-batches-75ffa389cd7?source=rss----3a

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Lists list list I love lists, just about everything can be a list of something. There are a thousand ways to solve problems with lists. Let’s talk about de-duping a long list and then cutting up that list into batches.The problem encountered was a list of some 60,000 IDs and in that list there were 3 dupes. Then after getting a clean list, that list needed to be batched up with 5000 IDs per batch.The initial idea was to build iterating loops to cycle through the list to find the dupes, using a recursive loop in a loop. This was going to be tedious and perhaps 15 lines of code, pretty standard stuff. To the google, and of course, ended up on stack overflow. There is a python functionality called “set”.8.7. sets - Unordered collections of unique elements - Python 2.7.15 (...)

#programming #python3 #lists-of-lists #python-list

#python Pandas — Basics to Beyond
▻https://hackernoon.com/python-pandas-tutorial-92018da85a33?source=rss----3a8144eabfe3---4

Python Pandas — Basics to BeyondA tutorial walkthrough of Python Pandas LibraryFor those of you who are getting started with Machine learning, just like me, would have come across Pandas, the data analytics library. In the rush to understand the gimmicks of ML, we often fail to notice the importance of this library. But soon you will hit a roadblock where you would need to play with your data, clean and perform data transformations before feeding it into your ML model.Why do we need this blog when there are already a lot of documentation and tutorials? Pandas, unlike most python libraries, has a steep learning curve. The reason is that you need to understand your data well in order to apply the functions appropriately. Learning Pandas syntactically is not going to get you anywhere. Another (...)

#data-visualization #machine-learning #python-pandas #data-science

Implementing a Sequence-to-Sequence Model
▻https://hackernoon.com/implementing-a-sequence-to-sequence-model-45a6133958ca?source=rss----3a8

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Learn how to implement a sequence-to-sequence model in this article by Matthew Lamons, founder, and CEO of Skejul — the AI platform to help people manage their activities, and Rahul Kumar, an AI scientist, deep learning practitioner, and independent researcher.In this article, you’ll implement a seq2seq model (an encoder-decoder RNN) for a simple sequence-to-sequence question-answer task. This model can be trained to map an input sequence (questions) to an output sequence (answers), which are not necessarily of the same length as each other.This type of seq2seq model has shown impressive performance in various other tasks such as speech recognition, machine translation, question answering, Neural Machine Translation (NMT), and image caption generation.The following diagram helps you (...)

#keras #python #deep-learning #tensorflow #machine-learning

Uni-Variate, Polynomial and Multi-Variate Regression using OLS/Normal Equation Approach (A-Z)
▻https://hackernoon.com/uni-variate-polynomial-and-multi-variate-regression-using-ols-normal-equ

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Learn, Code and Tune…As I mentioned in my previous article:Implementation of Uni-Variate Linear Regression in Python using Gradient Descent Optimization from…apart from Gradient Descent Optimization, there is another approach known as Ordinary Least Squares or Normal Equation Method. This approach, by far is the most successful and adopted in many Machine Learning Toolboxes. There is a descriptive reason behind OLS/Normal Equation Method being successful and widely preferred for Gradient Descent, to which I will be coming in the latter half of this article. Firstly, let’s move on to the Approach and its Python Implementation, secondly, applying it on Practice Datasets and finally, describing intuitively that why this over-performs Gradient Descent.The Ordinary Least Squares approach for (...)

#data-science #data-visualization #machine-learning #calculus #python3

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

Logistic Regression in Python from scratch
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Logistic Regression in Python (A-Z) from ScratchClassification is a very common and important variant among Machine Learning Problems. Many Machine Algorithms have been framed to tackle classification (discrete not continuous) problems. Examples of classification based predictive analytics problems are:Diabetic Retinopathy: Given a retinal image, classify the image (eye) as Diabetic or Non-Diabetic.Sentiment Analysis: Given a sentence, analyze the sense of the sentence (for ex. happiness/sadness, praise/insult, etc.)Digit Recognition: Given an image of a digit, recognize the digit (0–9). This is an example of Multi-Class Classification.and many more…Problems 1 and 2 are examples of Binary Classification, where there are only 2 classes, Diabetic/Non-Diabetic and Happiness/Sadness or (...)

#data-visualization #data-science #machine-learning #python3 #logistic-regression

Major #programming Trends to Prepare for in 2019
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The new year is always a great time for reflection on the past year, but also a time to look forward to the next year and to imagine what’s to come.For programmers, this is a good time to think about new skills you want to learn or interesting projects you want to take part in. Here at Indorse, we recently had a group discussion about what’s to come in 2019, and the team came up with some interesting ideas.Below we present some of the major programming trends to prepare for to help you stay at the top of your game in 2019 — but not before taking a look back at the key programming themes of 2018.A Look Back at Programming Trends in 2018Stack Overflow and GitHub both have extensive datasets on the most-used or most popular programming languages.The chart below from Stack Overflow shows the most (...)

#technology #python #javascript #coding

ConvNet from scratch : just lovely Numpy, Forward Pass |Part 1|
▻https://hackernoon.com/convnet-from-scratch-just-lovely-numpy-forward-pass-part-1-6d3a0776f90a?

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High level frameworks and APIs make it a lot easy for us to implement such a complex architecture but may be implementing them from scratch gives us the ground truth intuition of how actually ConvNets work.- Outline of the ArticleWe’ll be implementing the building blocks of a convolutional neural network! Each function we’ll implement will have detailed instructions that will walk you through the steps needed:Zero-PaddingConvolution forwardPooling forwardWe’ll use DLS jupyter notebooks to execute our modules. Check out DLS here. The fact is it comes with pre-installed libraries and frameworks required for Deep Learning. So it’s good to go for DL.A video walkthrough of Deep CognitionGenerate stories using RNNs |pure Mathematics with code|:Zero Padding•Zero padding adds zeros around the borders (...)

#deep-learning #machine-learning #technology #python #artificial-intelligence

Defense Against Dark Arts —The Mirror of Erised
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The Mirror of Erised from Harry Potter and the Sorcerer’s StoneAs in Harry Potter saga, we are surrounded by unknown Death Eaters (read Hackers) who are trying to attack poor Potter (read Client / Data) for one reason or another. Some time they want data (like Soccer’s stone or Prophecy in Order of Phoenix) or sometimes they just want to kill / corrupt Potter to fend off a threat / competition. In either case, we need to protect our Data and Deep Learning model from such kind of Dark Attacks.A regular Deep Learning model is very prone to attacks as it usually collects huge amount of data in a centralized server where deep learning models are trained. This is called centralized learning as learning occurs on a central server. But with a technique called Federated Learning, instead of (...)

#pytorch #deep-learning #python #ai #privacy

Who Carries Tech’s Top 100 Products of the Year? A Machine Learning Analysis.
▻https://hackernoon.com/who-carries-techs-top-100-products-of-the-year-a-machine-learning-analys

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BackgroundAs a junior data scientist, most of the times training data are ready for me to train the model (either by accessing database/external csv file provided). However, dataset is not always available for us, we need scraping skill to make our life easier.One Day ChallengeMy friend and I decided to start this mini-project which contains the whole process from scraping, to exploratory and finally perform some simple prediction using various machine learning models within 1 day as a small challenge for our own.We can’t wait to share our findings and hopefully you could enjoy reading it. Besides, feel free to reach us by commenting below if you find anything unclear/spot some points we have miss out! :)ObjectiveWhich platform provides most of the cheapest electronic gadgets.Performance (...)

#data-science #machine-learning-analysis #exploratory-data-analysis #data-analysis #python

Generating Lyrics Using Deep (Multi-Layer) LSTM
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Learn how to generate lyrics using deep (multi-layer) LSTM in this article by Matthew Lamons, founder, and CEO of Skejul — the AI platform to help people manage their activities, and Rahul Kumar, an AI scientist, deep learning practitioner, and independent researcher.This article will show you how to create a deep LSTM model suited for the task of generating music lyrics. Here’s your goal: to build and train a model that outputs entirely new and original lyrics that is in the style of an arbitrary number of artists. You can refer to the code file found at Lyrics-ai (▻https://github.com/PacktPublishing/Python-Deep-Learning-Projects/tree/master/Chapter06/Lyrics-ai) for this exercise.Data pre-processingTo build a model that can generate lyrics, you’ll need a huge amount of lyric #data, which (...)

#machine-learning #artificial-intelligence #python #deep-learning

#asyncio, the invincible
▻https://hackernoon.com/asyncio-the-invincible-16f5c4924755?source=rss----3a8144eabfe3---4

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Async programming is the new sexy when it comes to multitasking. It became famous with NodeJS but you can find libraries that support it in most major languages.For example in #python, the two most famous approaches are the usage of Tornado Web Server and the built-in library asyncio. For today we will do an introduction to the latter, as it has gone through tons of iterations and improvements lately and it is ready to charm people with its intuitive approach.What is async programming?It is a programming approach where we are vigilant when it comes to “dead time”. For example, if I/O is happening (eg I just sent a GET request, waiting for a response), the application can continue doing other stuff. Some people call it, the ideal secretary effect.It might not be for Python, but the (...)

#asynchronous

PEP 8016 — The Steering Council Model | Python.org
▻https://www.python.org/dev/peps/pep-8016

This PEP proposes a model of Python governance based around a steering council. The council has broad authority, which they seek to exercise as rarely as possible; instead, they use this power to establish standard processes, like those proposed in the other 801x-series PEPs. This follows the general philosophy that it’s better to split up large changes into a series of small changes that can be reviewed independently: instead of trying to do everything in one PEP, we focus on providing a minimal-but-solid foundation for further governance decisions.

Après la démission en juillet de son inventeur Guido van Rossum du poste de #dictateur_bienveillant_à_vie*, #Python vient de se doter d’une sorte de constitution, décidée par un vote Condorcet
▻https://discuss.python.org/t/python-governance-vote-december-2018-results/546

* C’est de l’humour d’informaticien mais avec un fond de vérité, et comme tout leadership de fondateur cela finit par s’avérer plus ou moins toxique.

#gouvernance #programmer #logiciel_libre

Vaex: Out of Core Dataframes for Python and Fast Visualization
▻https://towardsdatascience.com/vaex-out-of-core-dataframes-for-python-and-fast-visualization-12

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Wouldn’t it be great if you could load a 1 TB data file instantly.

All this is possible with memory mapping, which is a technique where you tell the operating system that you want a piece of memory to be in sync with the content on disk. It is technically quite similar to a swap disk. If a piece of memory isn’t modified, or not used for a while, the kernel will discard it so that RAM can be reused.

#python #pandas dépassé par #vaex? @lazuly

1 Minute Read #17 -strings in #python*
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1 Minute Read #17: f-strings in Python*How long is a piece of string? If it is as long as the many ways to manipulate strings in Python, then it is mighty long indeed. Python 3.6, released in 2016, introduced a whole new way to format strings. Known as ‘formatted-string literals’, they are a much more efficient than anything that preceded them. For example below is a standard way of handling strings using .format :You can be cute with this, and change the order (the index) in which the variables are called:Endless fun can be had in this manner…however…there is another way:Note the use of the (f”Hello…”) here — the f can be capitalised to F(“Hello…”), and it tells Python that you wish to use previously declared variables in this string.f-strings disturb old-school Pythonistas who have got so very used (...)

#programming #python3 #coding #learning-to-code

Preprocess Keras Model for TensorSpace
▻https://hackernoon.com/preprocess-keras-model-for-tensorspace-ed5e4db9a2a1?source=rss----3a8144

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How to preprocess Keras model to be TensorSpace compatible for neural network 3D visualizationTensorSpace & Keras“TensorSpace is a neural network 3D visualization framework. — TensorSpace.org”“Keras is a high-level neural network API. — keras.io ”IntroductionYou may learn about TensorSpace can be used to 3D visualize the neural networks. You might have read my previous introduction about TensorSpace. Maybe you find it is a little complicated on the model preprocess.Hence today, I want to talk about the model preprocess of TensorSpace for more details. To be more specific, how to preprocess the deep learning model built by Keras to be TensorSpace compatible.Fig. 1 — Use TensorSpace to visualize an LeNet built by KerasWhat we should have?To make a model built by Keras to be TensorSpace compatible, (...)

#python #data-visualization #machine-learning #technology #javascript

#python Implementation of Optimal Sample Variance for Voyager 2’s Spaceflight
▻https://hackernoon.com/python-implementation-of-optimal-sample-variance-for-voyager-2s-spacefli

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A Python implementation of how to select a sample with maximal coverage of a population while minimising punishing-costs.18,000,000,000 km away, Voyager 2 left the warming afterglow of solar-winds from the sun that is the heliosphere, and ventured onwards towards interstellar #space.Since launching on the 20th August 1977, the spacecraft has enjoyed an expansive panorama of our solar system — observing Jupiter in 1979, Saturn from 1981 and Uranus towards the end of 1985.Given the vastness of space, it begs the question — if you have a limited selection spots available, how can you determine the best sample of a population?In this case, I assume the “best” to be a selection’s relative uniqueness against the entire population. For instance, how unique is Mars amongst all other planets in our solar (...)

#coding #programming #data-structures

Two pillars of automated testing
▻https://hackernoon.com/two-pillars-of-automated-testing-13d0c2c6a7c?source=rss----3a8144eabfe3-

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When your team has been asked to move fast and break things, methodological purity can fast give way to sprint-speed pragmatism. However, this phrase — once the credo of Facebook — doesn’t mean we can take risks in the QA department. It’s really an admonition for us to open our eyes to new opportunities instead of closing them and praying that things will stay the same. A kind of rallying cry to be disruptive and try (and discard, if necessary) new things quickly.What’s all this got to do with testing and QA?Quite a bit. In our experience, QA is one of the slowest moving disciplines across the development landscape. This goes for both the supply side and the demand side of the market. It’s rare for new testing technology to reach the market in the first place. And equally, it’s not so common for (...)

#ruby #python #cypress #javascript #automated-testing

Pourquoi mettre à jour son #Python (régulièrement)
▻https://makina-corpus.com/blog/metier/2018/pourquoi-mettre-a-jour-son-python-regulierement

Le début des années 2010 a vu des centaines d’articles parler du passage de Python 2 à Python 3. Cet article n’en est pas un.

#News_Item

10 Reasons to Learn #python in 2018
▻https://hackernoon.com/10-reasons-to-learn-python-in-2018-f473dc35e2ee?source=rss----3a8144eabf

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Who wants to become a Python Programmer?If you follow my blog regularly then you may be wondering that why am I writing an article to tell people to learn Python? Didn’t I asked you to prefer Java over Python a couple of years ago?Well, things have changed a lot since then. In 2016, Python replaced Java as the most popular language in colleges and Universities and since then it has never looked back.Python is growing and growing big time. If you read #programming and technology news or blog post then you might have noticed the rise of Python as many popular developer communities including StackOverFlow and CodeAcademy has mentioned the rise of Python as a major programming language. But, the biggest question is why should a programmer learn Python? Python is growing Ok, that’s great, but (...)

#learn-python #machine-learning #web-development