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AI Technology

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Deep Learning & Machine Learning

The Magic of 5 Lines of Code, 5-Line Machine Learning PyCaret: Giving AutoML Wings to Your Data Analysis Projects

Hello! Have you ever felt exhausted from writing the same repetitive code over and over again while analyzing data? ๐Ÿ˜ซ Now, give your projects wings with PyCaret! ๐Ÿš€ This course reveals the secret to automating most of the tedious and complex machine learning processes with just 5 lines of code. Here is how you will transform after taking this course! โœจ Master Real-World Projects: ๐Ÿ“ˆ Customer Purchase Prediction (Classification), ๐Ÿ“‰ Medical Cost Prediction (Regression), ๐Ÿงฉ Customer Grouping (Clustering), and โณ Airline Passenger Forecasting (Time Series)! You can build "real" problem-solving skills by following along with these 4 core projects. Equip Professional Skills: That's not all! ๐Ÿค– I'll also teach you expert skills like managing created models with MLOps and building an API server with just a few clicks. Isn't it amazing? Protect Your Work-Life Balance: Most importantly, I will drastically reduce your repetitive tasks so you can focus only on core analysis. Leaving work on time is a bonus! ๐Ÿ˜‰ Whether you are not yet familiar with coding or an active professional who wants to explosively increase productivity, everyone is welcome! ๐Ÿ‘‹ Shall we transform into a '10x faster data scientist' together?

(4.0) 2 reviews

42 learners

Level Basic

Course period Unlimited

  • haeyeomiso
Python
Python
automl
automl
Machine Learning(ML)
Machine Learning(ML)
mlops
mlops
AI
AI
Python
Python
automl
automl
Machine Learning(ML)
Machine Learning(ML)
mlops
mlops
AI
AI

What you will gain after the course

  • Machine Learning Workflow Automation: You can increase analysis speed by more than 10 times by automating the entire processโ€”from data preprocessing and model comparison to tuning and evaluationโ€”with just a few lines of code.

  • 4 Major Machine Learning Projects: Gain practical experience by solving real-world business problems, including customer purchase prediction (classification), medical expense prediction (regression), customer segmentation (clustering), and time-series forecasting.

  • Writing code like an expert: Beyond simple scripts, you will master the use of Object-Oriented Programming (OOP) APIs to reliably manage multiple experiments, enabling you to write more robust code.

  • 'Black Box' Model Interpretability: You will gain the ability to visually analyze why a model made certain predictions using the SHAP library and translate those findings into actionable business insights.

  • Acquiring Foundational MLOps Competencies: Learn how to track experimental processes with MLflow and prepare completed models for deployment by turning them into APIs and Dockerfiles with just a few clicks.

PyCaret, the data analysis cheat code ๐ŸŽฎ

Leave the coding to PyCaret, and let's just have fun with the data!

I clearly studied machine learning... but why is my code always so long and complex? ๐Ÿค” How can I make data analysis a bit more fun?

So, I've prepared this! ๐Ÿ’ช

This course will drastically reduce the time you spend struggling with coding and help you focus solely on the truly fun part: 'digging into data.' Let's make the entire process of machine learning modeling incredibly simple with a wonderful tool for AutoML called PyCaret.

๐Ÿ˜Ž What will you gain after taking this course?

  • Automated Modeling: From preprocessing to comparing dozens of models, finish it all in the time it takes to drink a cup of coffee โ˜•

  • Choosing a 'well-grounded' model: Use numbers, not 'gut feeling'! You will be able to confidently explain why this model is the right choice.

  • Clear Real-world Projects: By working with 4 types of real data, you can quickly build your own impressive portfolio.

  • Talking to the Model: "AI, why did you make this prediction?" You will be able to interpret the inner workings of the model, just like asking a question to AI and hearing its answer. (feat. SHAP)

  • Writing clean code: You'll also gain the know-how to write well-organized code that is easy to understand even when you look back at it later.

  • mlops: The headache of machine learning projects! You can learn how to operate the system

๐Ÿ•น Completing 4 Projects

Seeing is believing! Build your practical skills by tackling four hands-on projects yourself.

#1 Will this customer buy juice? (Classification)
Predict the customer's purchasing behavior.

๐Ÿ“‰ #2 How much will the medical expenses be? (Regression)

Predict people's medical expenses using data.๐Ÿงฉ

#3 Shall we divide customers into groups? (Clustering)

Group similar customers together to discover new characteristics.

โณ #4 How many passengers will there be in the future? (Time Series)

Let's predict the future using patterns from the past.

๐Ÿ™‹ If you are one of these people, you will find it especially interesting!

  • Those who know machine learning theory but felt lost when trying to translate it into code


  • Those who want to reduce repetitive coding and focus their energy solely on actual analysis


  • Those who want to impressively complete their own data analysis project and turn it into a portfolio.

Here is what you will learn.

Modeling automation skills

You can significantly reduce your analysis time by learning how to complete everything from complex preprocessing to comparing dozens of models with just a few lines of code. โ˜•

4 representative projects

  • Complete classification, regression, clustering, and time-series projects yourself using four different types of data!


Model Interpretation Skills

Learn how to look into the inner workings of why the AI made such a prediction and explain it to others with confidence. ๐Ÿง

Know-how for selecting the optimal model

You can develop the insight to choose the best model that perfectly fits your problem, based on accurate data and metrics rather than just 'intuition'. โœจ

Notes before taking the course

Practice Environment

  • The lectures are explained based on MacOS. Environment setup is explained for each OS.

Prerequisite Knowledge and Precautions

  • Basic Python syntax


Recommended for
these people

Who is this course right for?

  • Current Data Analysts/Scientists: Those who want to drastically reduce the time spent on repetitive modeling tasks and focus more on hypothesis testing and deriving insights.

  • Machine learning learners/job seekers: Those who know machine learning theory but have difficulty handling actual data and completing projects.

  • Developers/Planners/Marketers: Those who want to quickly prototype data-driven predictive models and apply them to their work while reducing the burden of coding.

Need to know before starting?

  • Python Basic Syntax

  • It is helpful to have a basic understanding of machine learning concepts such as classification and regression.

Hello
This is

Nice to meet you!

I am Haeyeo, someone who explores the infinite possibilities of AI and computer science and wishes to share that journey with all of you.

During my undergraduate years, my passion for my major was so intense that I was nicknamed a 'Computer Science Addict.' I graduated at the top of my class with a major GPA of over 4.4. I then earned my Master's degree in AI from Seoul National University and further deepened my expertise through a doctoral program.

However, as I felt as much of a fascination for solving real-world problems with AI as I did for theoretical exploration, I took a break from my doctoral studies to gain valuable hands-on experience by working on AI-based LLM and video analysis projects at a startup.

Currently, I am working as an LLM project developer and PM at one of the top three conglomerates in Korea, contributing to creating positive changes that AI technology will bring to our lives. I will generously share with you the challenges I faced, the problem-solving processes I went through, and the vivid know-how I gained in the field. I will be your reliable guide on this journey into the exciting world of AI.

Inquiries and Proposals: haeyeo.open@gmail.com

Curriculum

All

25 lectures โˆ™ (4hr 56min)

Published:ย 
Last updated:ย 

Reviews

All

2 reviews

4.0

2 reviews

  • abcd123123๋‹˜์˜ ํ”„๋กœํ•„ ์ด๋ฏธ์ง€
    abcd123123

    Reviews 330

    โˆ™

    Average Rating 5.0

    5

    100% enrolled

    • exquisite789731๋‹˜์˜ ํ”„๋กœํ•„ ์ด๋ฏธ์ง€
      exquisite789731

      Reviews 2

      โˆ™

      Average Rating 4.0

      Edited

      3

      76% enrolled

      The instructor explains by looking at the code and results already written in Notion without actually running the code. Personally, while the lecture content is clean and concise, it also felt a bit like being explained to by ChatGPT.

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