Thonny Reviews

1. steve

   | retired | almost 3 years ago
   I like Thonny

   I started an on-line python course that used Pycharm as its basis. I had previously used Thonny to look at code for various programs. I found Pycharm to be over-featured for a beginner like me. Thonny seems much more on my level so I am continuing the course using it instead. And successfully I might add.

Amazon SageMaker Reviews

Thonny mentions (108)

• FeedMyFurBabies – Send and Receive MQTT messages between AWS IoT Core and your micro-controller

  Install Thonny and run it. Then go to Tools -> Options, to configure the ESP32C3 device in Thonny to match the settings shown in the screenshot below. - Source: dev.to / 4 months ago

• Raspberry Pico Badger: Hardware Features and OS

  The recommended way to programm MicroPython on the Raspberry Pico is to use the Thonny IDE. Accessing the Badger with reveals the following file structure:. - Source: dev.to / 5 months ago

• Abstract Classes in Python

  Personally, I like to debug and step through code to see where I went wrong so I'm going to paste the code into my Thonny IDE. I like Thonny for small code challenges like this because it doesn't require setting up a whole project just to run and step through code. - Source: dev.to / 6 months ago

• Ask HN: Do you know any good coding platform for education?

  Thonny is designed speciffically for that purpose https://thonny.org . For beginners the main advantage is the easier install and maintainance, and the less intimidating/cluttered environment. IMHO it makes some decent tradeoffs, and it is an onramp for students evolving to VSCode or PyCharm when they feel ready. - Source: Hacker News / 7 months ago

• Macropad with KMK

  I use the serial console with a tool like Thonny to debug KMK/CircuitPython code on my device. Running something like import main; main.keyboard.go() usually prints a useful error message. Source: 11 months ago

Amazon SageMaker mentions (37)

• Quantum Convolutional Neural Networks

  Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. - Source: dev.to / 18 days ago

• Observations on MLOps–A Fragmented Mosaic of Mismatched Expectations

  Damn straight. Oh, wait, some vendors have claimed to build an end-to-end solution. But, meh, that’s marketing talk. Take, for example, a well-known platform like Amazon Sagemaker, which describes itself as “a fully managed service that brings together a broad set of tools to enable high-performance, low-cost machine learning (ML) for any use case.” It’s a great platform. My startup has even partnered with them.... - Source: dev.to / about 2 months ago

• Sentiment Analysis with PubNub Functions and HuggingFace

  At this point, probably everyone has heard about OpenAI, GPT-4, Claude or any of the popular Large Language Models (LLMs). However, using these LLMs in a production environment can be expensive or nondeterministic regarding its results. I guess that is the downside of being good at everything; you could be better at performing one specific task. This is where HuggingFace can utilized. HuggingFace provides... - Source: dev.to / 2 months ago

• Beginning the Journey into ML, AI and GenAI on AWS

  Generative Artificial Intelligence (GenAI) is a type of artificial intelligence that can generate text, images, or other media using generative models. AWS offers a range of services for building and scaling generative AI applications, including Amazon SageMaker, Amazon Rekognition, AWS DeepRacer, and Amazon Forecast. AWS has also invested in developing foundation models (FMs) for generative AI, which are... - Source: dev.to / 5 months ago

• Technical Architecture for LLMOps

  Amazon and Azure already have much of what you're talking about in AWS SageMaker and Azure MLOps. Source: about 1 year ago