Notice
Recent Posts
Recent Comments
Link
일 | 월 | 화 | 수 | 목 | 금 | 토 |
---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | ||
6 | 7 | 8 | 9 | 10 | 11 | 12 |
13 | 14 | 15 | 16 | 17 | 18 | 19 |
20 | 21 | 22 | 23 | 24 | 25 | 26 |
27 | 28 | 29 | 30 | 31 |
Tags
- 프롬프트 엔지니어링
- 챗지피티
- AI 트렌드
- Supervised Learning
- nlp
- 인공신경망
- neural network
- 머신러닝
- learning algorithms
- Unsupervised Learning
- feature engineering
- Andrew Ng
- GPT
- 딥러닝
- Scikitlearn
- bingai
- prompt
- Regression
- AI
- supervised ml
- LLM
- Machine Learning
- 언어모델
- coursera
- 인공지능
- llama
- ML
- feature scaling
- Deep Learning
- ChatGPT
Archives
- Today
- Total
목록prompt (1)
My Progress

1. Linear Regression Purpose: To predict the output based on the given examples or dataset 1. 1 Terminology Univariate linear regression: Linear regression with one(single feature x) variable fw,b(x) = wx + b 1.2 Code Necessary Libraries #Numpy, a popular library for scientific computing import numpy as np #Matplotlib, a popular library for plotting data import matplotlib.pyplot as plt x_train =..
AI/ML Specialization
2023. 7. 26. 16:45