[PL 0301] Python Virtual Environment and Anaconda
Learn virtual environment concepts and setup methods.
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Hello students 😃
From basics to professional level, systematically covering deep learning - [Shin Kyungsik's Deep Learning] fourth lecture [Gradient-based Linear Regression (2)] is now open!
(Course Link: https://inf.run/ymv1P)
This is a lecture where you learn how to implement the code directly implemented in Gradient-based Linear Regression (1) into practical code using PyTorch's features. It is also a lecture where you theoretically learn about the necessity of data preprocessing, theory, and its impact on learning, and implement it with practical code.
Those following my All About AI curriculum would benefit from taking advantage of the open discount period😃
Additionally, the follow-up lecture [Gradient-based Linear Regression (3)] is scheduled to open sometime next week.
I will always do my best so that we can work together diligently to create a deep learning world!
Thank you.
Best regards, Shin Kyung-sik
Hello students 😃
From basic to professional level, systematically covering deep learning - [Shin Kyung-sik's Deep Learning] third lecture [Gradient-based Linear Regression (1)] is now open!
(Course Link: https://inf.run/KgQoQ)
This lecture covers the process of training the simplest model on data, based on the previously opened [Gradient Descent].
We're currently offering an opening commemoration discount, so those following my curriculum should take advantage of this period to register for the course😃
Additionally, the follow-up lecture [Gradient-based Linear Regression (2)] is scheduled to open this week.
I will always do my best so that we can work together diligently to create a deep learning world!
Thank you.
Best regards, Shin Kyung-sik
Hello students 😃
From basic to professional level, systematically covering deep learning - [Shin Kyung-sik's Deep Learning] second lecture [Gradient Descent] is now open!
(Lecture Link: https://inf.run/bK5xe)
This lecture is based on the previously opened [Gradients and PyTorch's Autograd] and covers the most fundamental learning algorithm in deep learning,
It focuses intensively on gradient descent.
Currently offering an opening commemoration discount, so those following my curriculum should take advantage of this period to register for the course😃
Additionally, the next lecture [Gradient-based Linear Regression (1)] is scheduled to open this weekend.
I will always do my best so that we can work together diligently to create a deep learning world!
Thank you.
Best regards, Shin Kyung-sik
Hello everyone, students!
Starting today, we're launching our full-scale deep learning course curriculum, so we're here to guide you😃
The [Shin's Deep Learning (ShinDL)] curriculum that I personally create covers deep learning systematically from the basics to actual paper-level lectures,
This is a curriculum with the goal of perfectly understanding deep learning technology by directly implementing all the techniques yourself!
Additionally, since the field of deep learning is so broad, the course is structured as modularized lectures covering specific topics rather than large-volume lectures.
This newly opened course is the first lecture in the [Shin Kyung-sik's Deep Learning] curriculum, designed to properly understand deep learning
A course that teaches 'differentiation', an essential mathematical foundation, and PyTorch framework's autograd technology
[Gradients and PyTorch's Autograd]입니다.
(Course Link: https://inf.run/wZoxE)
Going forward, we plan to cover not only basic deep learning techniques but also conduct practical projects based on deep learning papers.
If you are preparing to study deep learning, please follow the curriculum step by step starting from this lecture😃
Additionally, please note that the second deep learning lecture [Gradient Descent] is scheduled to open next week!
I will do my best to provide even better lectures in the future!
Thank you.
Best regards, Shin Kyung-sik
Lecture Opening Announcement
Hello! I am instructor Shin Kyung-sik 😃
I hope that all of you achieve your goals in 2025.
Today, a lecture covering Matplotlib, the most important library for those who deal with data, has opened!
The title of the lecture is [Python for Data Visualization - Matplotlib Master Class] .
As it is an essential library not only for my lectures but also for those learning data science,
We recommend that you take advantage of the open discount period to apply for classes!
Event Guide
I plan to start deep learning lectures in earnest with this next lecture.
We are working hard to prepare content that is incomparable to other deep learning educational content.
However, in order for you to take all the contents of these deep learning lectures,
You should have a solid foundation in NumPy and Matplotlib as well as basic Python grammar.
To support you on your journey to becoming a deep learning expert, we are holding the following event 😃
To those who complete both [NumPy Master Class] and [Matplotlib Master Class] by February 28, 2025
We are giving away a ⭐ ️50% discount coupon ⭐ ️ for [Gradient Descent Algorithm], the first lecture of the Deep Learning curriculum.This event is a course to build the basics that those studying machine learning and deep learning may find somewhat loose.
I'm doing this to give you some motivation.
I hope you all achieve the event 😃
How to participate
Please check the following Google form.
https://forms.gle/JVGE4M1scVeeFXPq6
Outro.
Please refer to the following curriculum for future deep learning lectures!
https://miro.com/app/board/uXjVNJ8PZSs=/
For reference, the design for the initial part of deep learning has been completed.
such as object detection, image segmentation, and transformer.
We will try to prepare detailed contents quickly~!
I hope you all do your best 😃
Neurotic Dream
Hello students!
Next week, a [NumPy Master Class] lecture that focuses on learning “NumPy,” the most important library for learning machine learning and deep learning, is scheduled to open.
In line with this, we would like to hold a course review event to commemorate the opening of the course.
I will randomly select 2 students who leave a sincere review of all my lectures currently open on Infraon and issue them a free coupon for the corresponding lecture (worth 45,000 won).
(To prevent abusing, please write after achieving a “progress rate” of 30% or more !)
After leaving a course review, please enter your Inflearn ID and the email address to receive the free coupon in the Google form below.
https://forms.gle/RcHcsbFrPAPYayAo6
The winner will be announced the day after the next week's lecture opens 😃
I would like to express my sincere gratitude to all the students who have always believed in my lectures and followed along diligently.
We will continue to work hard to create great lectures in the future!
Note) List of currently open courses
Free humanity from mathematics (Basic Algebra)
Free humanity from mathematics (Calculus Part.I) - Differential Calculus
Free humanity from mathematics (Linear Algebra Part.I) - Vector Geometry
LaTeX tutorial for writing equations
Python Level 1 for Artificial Intelligence
Python Level 2 for Artificial Intelligence
Python Debugging Basics
Python Level 3 for AI - Functions
Python Level 4 for AI - Objects and Classes
Python Virtual Environment and Anaconda
