
すべてのための大規模言語モデル LLM (Large Language Model) Part 1 - Llama 2 Fine-Tuning 試す
AISchool
LLM(Large Language Model)の基礎概念から、高性能LLMであるLlama 2モデルを、私が望むデータセットにFine-Tuningする方法まで、次々と学習します。
중급이상
LLM, Llama, Deep Learning(DL)
Learn the basics of machine learning step by step through various Kaggle examples, and learn vivid project experiences and practical tips from hard-to-access field machine learning engineers all at once.
Concept of machine learning
How to improve machine learning model performance
How to use Google Colab
Machine learning libraries - scikit-learn, xgboost
Machine Learning/Data Analysis Library - Numpy, Pandas
Data visualization library - matplotlib, seaborn
How to proceed with a machine learning practical project
Learn the basics of machine learning with various Kaggle examples.
Practical tips from working engineers, all in one place! 😀
0. What is Machine Learning (ML)?
1. A simple practice environment that does not require complex installation.
2. Introduction to scikit-learn & My First Machine Learning Model
3. Introduction to Kaggle and Kaggle Competition
4. Linear Regression Algorithm (Ridge, Lasso, ElasticNet) & How Much is My House Worth?
5. Random Forest, a popular and powerful predictor
6. XGBoost, the algorithm favored by Kaggle winners
7. Practical Stories from a Machine Learning Engineer
8. Practical DS/ML Tips from Professionals
Who is this course right for?
For those who are new to machine learning
Anyone who wants to learn data analysis techniques
Anyone who wants to get a job as a machine learning engineer
Anyone curious about the work process after getting a job as a machine learning engineer
Anyone who wants to get practical tips from machine learning engineers working at large IT companies
Need to know before starting?
Basic Python experience
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Reviews
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Answers
4.6
Rating
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60 lectures ∙ (7hr 19min)
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22 reviews
4.6
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5
基礎をよく握ることができました。
こんにちは。貴重な時間を割いて受講していただきありがとうございます~!詳しい受講評もありがとうございます~。より満足のいく講義を制作できるよう努力します。良い一日を過ごしてください!
$46.20
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