#numpy

[amarantine-amirite]

#art #artists on tumblr #glitch #glitch art #python #numpy

[devhubby]

#python #numpy #programmers #programming #devhubby

[a-fox-studies]

Day 2 - 14th May, 2023

Today I learned about data types in NumPy, and also the different ways of type casting. It was a short study session, because I went out for lunch :P and also had a terrible flare afterwards.

The output of the code above is [ 1 2 3 ] as it converts the floating values into integer values.

🎧 321 blast off - PmBata

#dailyfoxposts #30 days of productivity #30 dop #30doc #studyblr #study #studyspo #codeblr #coding #snappify #python #numpy

[pythonbaires]

Aprende a analizar datos con python!

En este curso aprenderás cómo analizar datos en Python usando matrices multidimensionales en numpy, a manipular DataFrames en pandas, a usar la biblioteca SciPy de rutinas matemáticas y a realizar aprendizaje automático usando scikit-learn. Comienza ya mismo! Pasarás de comprender los conceptos básicos de Python a explorar muchos tipos diferentes de datos a través de clases, laboratorios…

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#analisis de datos #Bibliotecas #curso #curso online #DataFrames #datos #numpy #online #Pandas #programacion #python

[womaneng]

Why NumPy?

So in data science what is the thing we deal with?

Data, right?

Yes, and how do we store the data?

Array? List? Dictionary?

Right.. Now think here we’re dealing with tons and tons of data and the data where we’re storing is super slow. What is gonna be the experience?

Terrible.

Absolutely, and that is why we use NumPy. In data science NumPy is the fundamental package to perform high-level mathematical computations on multi-dimensional arrays. So we store the data in NumPy arrays, and use NumPy to perform those computations. . . .

#numpy #datascientist #dataanalyst #pythonprogramming #codingdays #techbloggerlife #codingbook #womanegineer #freedatasciencebook #datascience #fyp #techinterview #learntocode #algorithms #softwarengineer #developer #yazilim #bilgisayarmuhendisligi

[mabeloid]

can someone who's better at coding please tell me what this bug is

(chessgamesarr is a dtype=str numpy array)

why is it cutting the last two characters off why is it doing that i thought it might be a character limit thing but that only is 58->56 long that would be a weird number to cut off at

#numpy #python #programming help

[fortunatelycoldengineer]

#NumPy #numpy #pytorch #pythoncode #python #pythonprogramming

[pythongui]

Numpy:A Powerful Python Library| Python GUI

NumPy is a vital Python library for numerical computations, offering robust tools for array operations and mathematical functions. Widely adopted in data science and engineering, NumPy optimizes computational tasks with its efficient array-based operations, making it indispensable for scientific computing and data manipulation. To learn more about the details, please visit our website.

#python gui #NumPy

[learning-path]

Exploring NumPy: From Basics to Advanced Techniques

Master NumPy with ease! Our guide delves into array manipulation, math functions, and data analysis. Whether novice or expert, unlock the full potential of Python. #NumPy #Python #NumPy #DataAnalysis #MachineLearning

NumPy, short for Numerical Python, is a fundamental package for scientific computing in Python. It provides support for arrays, matrices, and a host of mathematical functions to operate on these data structures. This blog post will guide you through the basics of NumPy and its powerful features. Step 1: Check Python Installation Step 2: Install NumPy Step 3: Verify NumPy Installation Step 4:…

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#data-science #django #machine-learning #numpy #p4n #programming #python

[codeexpertinsights]

Today, Python is one of the most prominent programming languages for web applications. Whether it’s building an AI and ML application or making an app with Django web development, Python is gaining global popularity. You can use Python for building scalable and rapid web applications. From ERP apps to B2C web apps, a Python development company can develop all kinds of applications for you. Python Development Companies are gaining popularity in the global development market. Python is a dynamic, object-oriented, and undoubtedly, a veteran programming language. Python Development Companies understand that this programming language enables the swift completion of tasks, allowing you to merge systems effectively.

#python developers #pycharm #numpy

[eyssant]

Master Python: Guide to Learning Python Online

Python has emerged as one of the most popular programming languages, known for its simplicity, versatility, and readability. Whether you're a beginner or an experienced programmer, learning Python opens up a world of opportunities in software development, data science, machine learning, and web development. With the abundance of online resources available, mastering Python has never been easier. In this guide, we will explore how you can effectively learn Python online.

1. Choose the Right Learning Platform

There are numerous online platforms offering Python courses, tutorials, and resources. Some of the most popular ones include:

Coursera: Offers Python courses taught by instructors from top universities and organizations.

edX: Provides Python courses from universities like MIT, Harvard, and others.

Udemy: Offers a wide range of Python courses at different skill levels.

Codecademy: Offers interactive Python tutorials suitable for beginners.

Microsoft: Provides free Python tutorials and projects for beginners.

2. Start with Fundamentals

If you're new to programming, it's essential to start with the fundamentals of Python. Focus on understanding basic concepts such as variables, data types, loops, conditionals, functions, and object-oriented programming principles. Many online courses and tutorials are specifically designed for beginners and provide a solid foundation in Python programming.

3. Hands-on Practice

Learning Python is not just about reading tutorials or watching videos; it's about hands-on practice. Make sure to write code regularly to reinforce your understanding of concepts and improve your problem-solving skills. Work on coding exercises, challenges, and projects to apply what you've learned and build confidence in your programming abilities.

4. Join Online Communities

Joining online communities and forums dedicated to Python can be incredibly valuable. Platforms like Stack Overflow, Reddit's r/learnpython, and Python-related Discord servers are great places to ask questions, share knowledge, and connect with other Python enthusiasts. Engaging with the community can help you stay motivated, gain insights from experienced developers, and troubleshoot issues you encounter while learning Python.

5. Build Projects

One of the most effective ways to learn Python is by working on real-world projects. Identify projects that align with your interests and apply your Python skills to solve problems or create something meaningful. Building projects not only reinforces your understanding of Python but also helps you develop practical experience and a portfolio to showcase your skills to potential employers or clients.

6. Explore Advanced Topics

Once you've mastered the basics of Python, you can explore more advanced topics based on your interests and career goals. These may include web development using frameworks like Django or Flask, data analysis and visualization with libraries like Pandas and Matplotlib, machine learning and artificial intelligence with libraries like TensorFlow and PyTorch, or automation and scripting for various tasks.

7. Stay Updated

The field of programming is constantly evolving, and Python is no exception. Stay updated with the latest developments, new features, and best practices in Python programming. Follow influential Python developers, subscribe to Python-related blogs and newsletters, and participate in online courses or webinars to keep your skills sharp and up-to-date with industry trends.

Conclusion

Learning Python online offers a flexible and accessible way to acquire valuable programming skills. By choosing the right learning platform, starting with fundamentals, practicing regularly, joining online communities, building projects, exploring advanced topics, and staying updated, you can master Python and unlock a world of opportunities in the ever-growing field of technology. Whether you're pursuing a career in software development, data science, or any other field, proficiency in Python is a valuable asset that can propel your success in the digital age. Happy coding!

#python #numpy #programming

[a-fox-studies]

Day 1 - 13th April, 2023

A wise someone (@compooter-blob) told me that NumPy, Pandas and Matplotlib are the butter, bread and milk of python development.

I started learning a bit of NumPy today, and I only have one word to describe it - cute.

#dailyfoxposts #studyblr #30dop #30 days of productivity #tumblr challenges #studyblr challenges #study #studyspo #codeblr #coding #python #numpy #python numpy

[dailyaspirants]

Python Ternary Operator

Visit our site for free project source codes-- dailyaspirants.com . . Follow @dailyaspirants for more content on website development, programming languages like Python, PHP, SEO, Free tools..etc.

#pythonhub #pythonprogramming #python3 #programming #pythonprojects #pythonbeginner #coding #chatgpt #AI #codingforkids #CodingisFun #codinglife #html #html5 #css #Code #dailyaspirants #numpy

[abhishek-21]

Welcome to our comprehensive NumPy course, where you will delve into the world of this powerful library and learn how to efficiently work with arrays, perform mathematical operations, and tackle complex data analysis tasks.

#numpy

[fortunatelycoldengineer]

#pytorch #numpy #python #pythonprogramming #pythoncode #pythondeveloper

[kodakademi]

Python ile Makine Öğrenmesi

Makine Öğrenmesi Nedir?

Makine öğrenmesi, bilgisayar sistemlerinin deneyimlerinden öğrenmesine izin veren bir yapay zeka dalıdır. Python, makine öğrenmesi uygulamaları için popüler bir dil olmuştur. İlk adım, temel Python bilgisini edinmektir. Ardından, kütüphaneler aracılığıyla veri analizi ve model oluşturma süreçlerini öğrenmek, makine öğrenmesinde başarı için temel adımlardan biridir.

Python Dilinin Makine Öğrenmesindeki Rolü

Python, basit syntax yapısı ve geniş kütüphane desteği nedeniyle makine öğrenmesi uygulamaları için ideal bir dil olarak öne çıkmaktadır. NumPy, Pandas ve Scikit-Learn gibi kütüphaneler, veri manipülasyonundan model eğitimine kadar birçok alanda güçlü araçlar sunar. Python dilini kullanmak, karmaşık algoritmaları anlama ve uygulama sürecini daha erişilebilir hale getirir.

Temel Makine Öğrenmesi Algoritmaları ve Python

Python ile makine öğrenmesi çalışmalarına başlamadan önce temel algoritmaları anlamak önemlidir. Regresyon, sınıflandırma ve kümeleme gibi yaygın algoritmalar, veri setlerini anlamak ve modelleri doğru bir şekilde uygulamak için temel gerekliliklerdir. Python, bu algoritmaları kolayca uygulamak ve sonuçları görselleştirmek için geniş bir araç seti sunar.

Python ile Makine Öğrenmesinde İleri Seviye Uygulamalar

Python, makine öğrenmesi dünyasında ileri düzey uygulamalara da olanak tanır. Derin öğrenme ve büyük veri işleme gibi konularda uzmanlaşmak, Python dilinin sunduğu geniş ekosistem sayesinde daha da kolay hale gelir. TensorFlow ve PyTorch gibi derin öğrenme kütüphaneleri, karmaşık sinir ağlarını uygulamak için güçlü araçlar sunar. Bu nedenle, Python ile makine öğrenmesi dünyasında ileri seviyede uzmanlık kazanmak için sürekli öğrenme ve pratik yapma önemlidir.

Veri Analizi Proje Yönetimi ve Problem Tipleri

Veri analizi, makine öğrenmesi süreçlerinin temel bir parçasıdır ve projelerin başarılı bir şekilde yönetilmesi için etkili bir strateji gerektirir. Python, veri analizi projelerinde kullanılmak üzere çeşitli kütüphaneler ve araçlar sunar. Pandas, NumPy ve Matplotlib gibi kütüphaneler, veri setleri üzerinde etkili analizler yapmak ve sonuçları görselleştirmek için kullanılır.

Proje yönetimi, veri analizi süreçlerini düzenlemek ve hedeflere ulaşmak için kritik bir unsurdur. Bu süreç, veri toplama, temizleme, keşifsel veri analizi (EDA), model oluşturma ve sonuçları yorumlama adımlarını içerir. Python, bu aşamalarda kullanılan bir dizi kütüphane sayesinde bu süreçleri daha verimli hale getirir.

Veri analizi projeleri genellikle çeşitli problem tiplerini içerir. Sınıflandırma, regresyon, kümeleme ve boyut azaltma gibi temel problem tipleri, projenin doğasına bağlı olarak farklılık gösterir. Python, bu problem tiplerine özgü olarak geliştirilmiş kütüphaneleri içerir. Örneğin, Scikit-Learn kütüphanesi sınıflandırma ve regresyon modelleri oluşturmak için kullanılırken, K-means gibi algoritmaları içeren başka bir kütüphane de kümeleme problemleri için tercih edilebilir.

Sonuç olarak, Python dilini veri analizi projelerinde etkili bir şekilde kullanmak, projenin her aşamasını yönetmek ve farklı problem tipleri için uygun araçları seçmek, başarılı bir makine öğrenmesi uygulaması için kritik öneme sahiptir. Bu noktada, veri analizi projelerindeki yönetim stratejilerini ve karşılaşılabilecek farklı problem tiplerini anlamak, Python dilini kullanarak daha sağlam ve optimize edilmiş makine öğrenmesi uygulamaları oluşturmanıza yardımcı olacaktır.

Kaynak : Python ile Makine Öğrenmesi – Kod Akademi (kodyazilimakademisi.com.tr)

#Matplotlib #NumPy #Pandas #PyTorch #TensorFlow