I'm not struggling with the theories and the use case. I just don't really know how to code but I understand the purpose of most part of a code when I check through it but to create a fully fledged code of mine from scratch is my really big problem
Thank you for watching! I would recommend breaking it down to tasks. Starting with data preparation, look for what features you want the models to be trained on. If you need to clean the dataset, read up on how people do it. I find that breaking down tasks to sub tasks help a lot! And lastly, practice practice practice. Never give up!
Machine learning is literally a struggle to learn because it involves mastering complex mathematical concepts, dealing with vast amounts of data, and staying updated with rapidly evolving technologies. The steep learning curve, combined with the need for hands-on experience and problem-solving skills, can make the journey challenging yet rewarding.
The math :( I actually did very well in calculus courses in college and enjoyed calc but I find I have this internal panic when I try to get back into math after feeling like I was bad at math for YEARS during childhood and primary education. I love coding and have a PhD in evolutionary bio so have done a lot of work with large data sets and analyses in R/python and feel comfortable with many aspects but I freeze when getting into the hardcore maths behind it all. Do you have any suggestions for accessible courses/texts?
I would look at "Essential Math for ML" to start with and then go for something like "Fundamental Mathematics for ML in Science". I think you raise a great point about math in ML.
I'm not struggling with the theories and the use case. I just don't really know how to code but I understand the purpose of most part of a code when I check through it but to create a fully fledged code of mine from scratch is my really big problem
Thank you for watching! I would recommend breaking it down to tasks. Starting with data preparation, look for what features you want the models to be trained on. If you need to clean the dataset, read up on how people do it. I find that breaking down tasks to sub tasks help a lot! And lastly, practice practice practice. Never give up!
I think I should work on that.
Believe me, you will get better!
Its hard because most people dont undetstand mathematics.
Machine learning is literally a struggle to learn because it involves mastering complex mathematical concepts, dealing with vast amounts of data, and staying updated with rapidly evolving technologies. The steep learning curve, combined with the need for hands-on experience and problem-solving skills, can make the journey challenging yet rewarding.
Yes indeed! It’s a long journey.
I really needed this type of video, thank you
Thank you for watching. Glad I could help!
The math :( I actually did very well in calculus courses in college and enjoyed calc but I find I have this internal panic when I try to get back into math after feeling like I was bad at math for YEARS during childhood and primary education. I love coding and have a PhD in evolutionary bio so have done a lot of work with large data sets and analyses in R/python and feel comfortable with many aspects but I freeze when getting into the hardcore maths behind it all. Do you have any suggestions for accessible courses/texts?
I would look at "Essential Math for ML" to start with and then go for something like "Fundamental Mathematics for ML in Science". I think you raise a great point about math in ML.
Great video!
Glad you enjoyed it!