The size of the data you can load and train in your local computer is typically limited by the memory in your computer. Let’s explore various options of how to deal with big data in python for your ML projects. In certain situations, you might have a hard time working on large data, that is …
How to deal with Big Data in Python for ML Projects (100+ GB)? Read More »
Decorators in python allow you to dynamically change the functionality of another function, without altering it’s code. What? Is that possible? Yes. This covers: 1. What is a decorator and how to create one? 2. Easier way to decorate functions 3. Class decorators 4. Problem with docstrings on decorated functions and how to solve. What …
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Generators in python provide an efficient way of generating numbers or objects as and when needed, without having to store all the values in memory beforehand. Introduction You can think of Generators as a simple way of creating iterators without having to create a class with __iter__() and __next__() methods. So how to create a …
Generators in Python – How to lazily return values only when needed and save memory? Read More »
Iterable in Python is any object that can be looped over. In order for an iterable to be looped over, an iterable needs to be converted to an iterator using the __iter__() method. Once created, it is actually the iterator that gets iterated over. This is also what happens internally when you run a for-loop. …
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Any Python file with a .py extension is a Module in Python. A python package is a collection of such modules along with a __init__.py file. Let’s understand how to work with modules and packages with clear examples. Introduction When you work on python projects, it’s not a good practice to have all you python …
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Object oriented programming is an effective way of writing code. You create classes which are python objects, that represented meaningful entities which defines its own behaviour (via methods) and attributes. Let’s understand what a class is and the concepts behind Object Oriented Programming in Python Everything you have encountered so far in Python, such as …
How to use numpy.random.rand() function ? numpy.random.rand() function is used to generate random float values from an uniform distribution over [0,1). These values can be extracted as a single value or in arrays of any dimension. In this article, you will learn about various use cases of this function. Structural overview of numpy.random.rand() Syntax: numpy.random.rand(d0, …
How to reshape a numpy array? The numpy.reshape() function is used to reshape a numpy array without changing the data in the array. It is a very common practice to reshape arrays to make them compatible for further calculations.
Vaex Python is an alternative to the Pandas library that take less time to do computations on huge data using Out of Core Dataframe. It has fast, interactive visualization capabilities as well. Pandas is the most widely used python library for dealing with dataframes and processing. The popularity is due to the convenient, easy to …
Modin is a python library that can be used to handle large datasets using parallelisation. The syntax is similar to pandas and its astounding performance has made it a promising solution. By changing just one line of code. This article shows you why you should start using Modin and how to use it with hands-on …
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Dask provides efficient parallelization for data analytics in python. Dask Dataframes allows you to work with large datasets for both data manipulation and building ML models with only minimal code changes. It is open source and works well with python libraries like NumPy, scikit-learn, etc. Let’s understand how to use Dask with hands-on examples. Dask …
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The Global Interpreter Lock (GIL) of Python allows only one thread to be executed at a time. It is often a hurdle, as it does not allow multi-threading in python to save time. This post will tell you what exactly is GIL and why is it needed. This will also walk you through the alternate …
What does Python Global Interpreter Lock – (GIL) do? Read More »
tf.function is a decorator function provided by Tensorflow 2.0 that converts regular python code to a callable Tensorflow graph function, which is usually more performant and python independent. It is used to create portable Tensorflow models. Introduction Tensorflow released the second version of the library in September 2019. This version, popularly called …
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Lambda Function, also referred to as ‘Anonymous function’ is same as a regular python function but can be defined without a name. 1. What is Lambda Function in Python? Lambda Function, also referred to as ‘Anonymous function’ is same as a regular python function but can be defined without a name. While normal functions are …
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Adding yield keyword to a function will make the function return a generator object that can be iterated upon. What does the yield keyword do? Approaches to overcome generator exhaustion How to materialize Generators? How yield works, step by step Exercise 1: Write a program to create a generator that generates cubes of numbers up …
Compare the popular deep learning frameworks: Tensorflow vs Pytorch. We will go into the details behind how TensorFlow 1.x, TensorFlow 2.0 and PyTorch compare against eachother. And how does keras fit in here. Table of Contents: Introduction Tensorflow: 1.x vs 2 Difference between static and dynamic computation graph Keras integration or rather centralization What is …
Reducing code runtime is important for developers. Python Profilers, like cProfile helps to find which part of the program or code takes more time to run. This article will walk you through the process of using cProfile module for extracting profiling data, using the pstats module to report it and snakeviz for visualization. By the …
Collections is a built-in python module that provides useful container datatypes. Container datatypes allow us to store and access values in a convenient way. Generally, you would have used lists, tuples, and dictionaries. But, while dealing with structured data we need smarter objects. In this article, I will walk you through the different data structures …
JSON stands for JavaScript Object Notation. JSON is a lightweight data format used for data interchange between multiple different languages. It is easy to read for humans and easily parsed by machines. CONTENTS Brief Overview Purpose of JSON Serializing JSON dumps() function dump() function Deserializing JSON loads() function load() function Complex number encoding Complex JSON …
Requests is an elegant and simple Python library built to handle HTTP requests in python easily. It allows you make GET, POST, PUT and other types of requests and process the received response in a flexible Pythonic way. Contents Introduction to Requests Library What is a GET and POST request? GET Method Status Code Contents …
Requests in Python Tutorial – How to send HTTP requests in Python? Read More »
