Lecture 5: Floats and Approximation Methods

MIT 6.100L Introduction to CS and Programming using Python, Fall 2022
Instructor: Ana Bell
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An introduction to simple algorithms, float types, and approximation methods. Floating point numbers introduce challenges as they can't be represented in memory exactly. Approximation methods use these floating numbers.
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[@MichaelAlexander1967]

At one point in time, many many years ago,, I had a really good understanding of base 10 and base 2 or binary numbers, but for some reason I'm not fully understanding all of Ana' sentences, in real time, so I'm going to have to replay this video, using the pause button often,, to ensure I'm grasping the logic and the patterns that she describes. But I do love the idea that she fully grasps and internalizes these concepts. That's why she's the CS professor at MIT. 💪🏼💪🏽🙌🏽💯%❤ A sincere thanks to MIT for posting OpenCoarseWare videos! Finally, my big question is: If I'm not able to logically recreate the process/algorithm and Python code for converting a base 10 decimal number into a base two binary decimal number, if I'm not able to easily/quickly do that, will I have severe struggles becoming a Python Software Developer or Software Engineer? I would imagine that once I can do that easily, I can use a similar algorithm to convert any base # to binary. Is that the idea? I've gotta really studg the binary representation of .625 😏😒🙏🏽 Oh, is this the kind of code or algorithm inside a calculator?

[@andiuptown1711]

To answer your question, no not at all. But also depends on what you’re using Python for, as many use it for mathematical fields like data science and ML/AI