Python Basics for Introduction to Machine Learning & Deep Learning,
If you want to finish the main points quickly 💎
Essential for artificial intelligence
3 hour Python properties course!
What about this lecture?
History of Artificial Intelligence Jupyter Notebook
Python Pandas Matplotlib
This course was created so that those who want to take the “Introduction to Machine Learning and Deep Learning using Python” and “Building Deep Learning Models using PyTorch” courses can acquire the basic knowledge of Python necessary in a short period of time.
Introduction to Machine Learning and Deep Learning Using Python
trimurti
Beginner / Machine Learning(ML), Deep Learning(DL), Python, Numpy, Pandas, Matplotlib, Anaconda, Tensorflow, Keras, CNN
Do you want to take your first step into the world of data? Learn machine learning and deep learning, the core technologies of AI, with Python. This course will guide you step by step, from the basics of machine learning and deep learning to practical applications. Traditional machine learning and deep learning are based on many of the same principles and technical systems. Therefore, this course does not separate the two into separate subjects, but rather organizes them into one connected course so that beginners can increase their understanding of machine learning as a whole.
Beginner
Machine Learning(ML), Deep Learning(DL), Python
Machine learning/deep learning have become a trend!
However, when you actually try to get started, it can feel overwhelming. In particular, the fact that you cannot start without knowing the basics of a programming language is a burden for many people.
'They say it's good to start from the basics of Python step by step, but I don't have enough time....'
'Can't we just cover the basics of Python, which are essential for implementing artificial intelligence, in properties?'
This course is designed for those people. Based on my experience teaching machine learning/deep learning for many years, I will help you acquire the Python knowledge necessary for machine learning in a short period of time through an accelerated course that extracts only the essential parts. Let's take on the challenge together?
Crash Course!
So that we can finish it quickly.
Let's quickly review the basic Python grammar in about 35 minutes.
We will also quickly organize the content necessary for getting started with actual machine learning/deep learning, such as NumPy, Pandas, Matplotlib, linear algebra, and feature scaling.
Check out the Q&A ! 💬
Q. But shouldn’t I take a proper language course?
Of course, that is the most ideal way to do it, but it takes a lot of time. If you spend about 5 weeks learning the entire Python language, 1 week learning Numpy, 1 week learning Pandas, and 1 week learning Matplotlib, you can gain beginner to intermediate skills. However, most of the content you study in that time is often needed in fields other than machine learning, so this lecture aims to deliver the core necessary for machine learning/deep learning in a short period of time.
Q. But wouldn’t it be better to start studying from the basics step by step?
If you have enough time, I highly recommend you do so. This course is designed for those who are short on time and feel burdened by the introduction to machine learning/deep learning due to the basic course.
![[Pytorch] Building Deep Learning Models with PytorchCourse Thumbnail](https://cdn.inflearn.com/public/courses/329226/cover/056ed444-5b26-40fc-b4d6-8e03b2f23890/DL_pytorch.jpg?w=420)
