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- RandomAffine in PyTorch
- ThiscodedemonstratestheRandomAffinetransformintorchvision.Itexploresvariousparametercombinations,showcasingitscapabilitiesforimagerotation,translation,scaling,andshearing.Theresultsarevisualizedusingmatplotlib.TheRandomAffinetransformallowsfortwo-dim
- Python Tutorial 894 2025-01-16 11:13:58
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- Artificial Neurons: The Heart of AI
- Therecentbreakthroughsinlargelanguagemodels(LLMs)haveignitedsignificantinterestinthefieldofartificialintelligence(AI).Thissurgeinpopularityhasledmanytopursuecareersinthisrapidlyexpandingsector.However,acrucialfoundationalelementoftenoverlookedisthear
- Python Tutorial 548 2025-01-15 22:44:44
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- Boolean types and expressions
- Studying Boolean data types and operations is an important aspect of programming. In this article, we will consider the key points: Decision-making process: Boolean value (true/false) is the basis of conditional operators (if, else), giving the code flexibility and adaptability. Code optimization: Boolean expressions
- Python Tutorial 213 2025-01-15 22:17:47
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- join my project semester simulator
- DiveintothechaoticandhilariousworldofSemesterSimulator,aPython-basedsimulationgamedesignedforComputerSciencestudents(andanyonewhoenjoysagoodchallenge!).Playersjuggleenergylevels,mentalhealth,finances,GPA,andprojectdeadlinesinafranticraceagainsttime.A
- Python Tutorial 868 2025-01-15 20:10:45
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- Building a String Calculator with Test-Driven Development (TDD): A Step-by-Step Guide
- WewillimplementastringcalculatorinPythonusingatest-drivendevelopment(TDD)approach.Thismeanswewillwritetestsforeachfeaturebeforeimplementingthecorrespondingfunctionality.Youcanrefertothelinkhttps://osherove.com/tdd-kata-1asyourcheckpointsforimplementi
- Python Tutorial 1023 2025-01-15 18:09:48
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- A Complete Beginner's Guide to Python Training Course
- Python:YourGatewaytoProgrammingSuccess–ABeginner'sGuidePython'sglobalpopularityasaversatileanddynamicprogramminglanguagemakesitanidealchoiceforaspiringprogrammersofalllevels.ThisguideprovidesacomprehensiveoverviewofPythontraining,outliningwhattoexpec
- Python Tutorial 354 2025-01-15 16:13:47
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- How to solve the problem of limited access speed of crawlers
- Datacrawlingoftenencountersspeedlimitations,impactingdataacquisitionefficiencyandpotentiallytriggeringwebsiteanti-crawlermeasures,leadingtoIPblocks.Thisarticledelvesintosolutions,offeringpracticalstrategiesandcodeexamples,andbrieflymentions98IPproxya
- Python Tutorial 495 2025-01-15 12:23:50
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- Solving Circular Dependencies: A Journey to Better Architecture
- MyHyperGraphproject'sgrowthexposedsignificanttechnicaldebt,primarilymanifestedascripplingcirculardependencies.Thishinderedmaintainabilityandtesting,promptingacompletearchitecturalrefactoring.Thispostdetailsthechallenges,theimplementedsolutions,andthe
- Python Tutorial 413 2025-01-15 10:57:48
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- Working with Files Asynchronously in Python using aiofiles and asyncio
- AsynchronouscodehasbecomeamainstayofPythondevelopment.Withasynciobecomingpartofthestandardlibraryandmanythirdpartypackagesprovidingfeaturescompatiblewithit,thisparadigmisnotgoingawayanytimesoon.Ifyou'rewritingasynchronouscode,it'simportanttomakesurea
- Python Tutorial 884 2025-01-15 09:52:44
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- The Complete Introduction to Time Series Classification in Python
- Timeseriesdataisubiquitousacrossnumerousindustries,yetwhiletimeseriesforecastingreceivesconsiderableattention,timeseriesclassificationisoftenoverlooked.Thisarticleprovidesacomprehensiveintroductiontotimeseriesclassification,exploringitsreal-worldappl
- Python Tutorial 689 2025-01-15 06:57:43
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- Simplify Python-Informix Connections with wbjdbc
- Introduction Managing JDBC connections and JVM settings can be tedious for Python applications, especially when using databases such as Informix. This is where wbjdbc comes in, a Python library designed to simplify these tasks. It automatically configures your environment so you can focus on the most important part: interacting with your data. This article walks you through the key features of wbjdbc, including how to automate connection setup, and provides practical examples for automating routine tasks. What is wbjdbc? wbjdbc is a Python library that simplifies JDBC and JVM setup, making it easy to connect to databases such as Informix. Its main features include: Simplified JVM initialization: self-
- Python Tutorial 385 2025-01-15 06:11:50
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- Pythonizing JavaScript
- Python has many powerful utility functions, such as range, enumerate, zip, etc., which are built on iterable objects and the iterator protocol. Combined with generator functions, these protocols have been available in all Evergreen browsers and Node.js since around 2016, but their usage is surprisingly low in my opinion. In this article, I will use TypeScript to implement some of these helper functions, hoping to change this situation. Iterators, Iterable Objects, and Generator Functions Iterator Protocol The iterator protocol is a standard way to generate a sequence of values. For an object to be an iterator, it must comply with the iterator protocol by implementing the next method, for example: co
- Python Tutorial 1042 2025-01-14 22:19:48
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- dvanced Python Web Crawling Techniques for Efficient Data Collection
- Asaprolificauthor,IinviteyoutoexploremyAmazonpublications.RemembertofollowmyMediumprofileforcontinuedsupport.Yourengagementisinvaluable!Efficientdataextractionfromthewebiscritical.Python'srobustcapabilitiesmakeitidealforcreatingscalableandeffectivewe
- Python Tutorial 406 2025-01-14 20:19:46
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- What are AI Agents ? and how can it help you ?
- AIAgents:YourAutonomousTaskMastersAIagentsarerapidlychanginghowwetackletasksandsolveproblems.ThispostexplainswhatAIagentsare,whattheydo,andhowtheycanbenefityou.UnderstandingAIAgentsSimplyput,anAIagentisasoftwareprogramdesignedtoworkindependentlytocom
- Python Tutorial 412 2025-01-14 20:14:48
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- Train LLM From Scratch
- I completed a complete LLM training project, from downloading the training data set to using the trained model to generate text, the entire process was included. Currently supports the PILE dataset, a diverse dataset for LLM training. You can limit dataset size, customize the default Transformer architecture and training configuration, and more. Here is an example of text generated by my LLM with 13 million parameters trained on a ColabT4 GPU: In ****1978 the park was returned to the factory - the public areas were separated by electric fences that followed where the station was located built for the city. Canals in ancient Western countries were restricted to urban areas. China's villages are directly connected to cities, sparking criticism of U.S. budget
- Python Tutorial 279 2025-01-14 20:13:45
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