2022-machine-learning-specialization's Issues
ModuleNotFoundError :No module named 'scipy' and NameError: name 'load_house_data' is not defined
Every time I run it, it pops up ModuleNotFoundError or NameError and so on. Probably because I didn't run successfully "pip install -r requirements.txt",I don't know. When I run this, it always comes up "error: subprocess-exited-with-error" and "exit code: 1".I don't know how to solve it. Can someone help me? Thank you very much!
C3_W2_RecSysNN_Assignment.ipynb NOT PASSED
Please add .gitignore
the .ipynb_checkpoints/
directory is generated automaticly by Jypyter notebook for temporary save. This directory is useless and may confuse beginners. So I suggest to add it into .gitignore
Why does output keep showing "loading widget" in C1_W1_Lab04_Cost_function_Soln?
执行pip install -r requirements.txt报错——pycurl
python:3.7.6(新建环境)
导入pip install -r requirements.txt报错
error code为1时可能需要执行:
pip install --upgrade setuptools
但是并没有解决我的问题:
在这个地址:https://download.lfd.uci.edu/pythonlibs/archived/cp37/pycurl-7.45.1-cp37-cp37m-win_amd64.whl
下载pycurl的whl,直接从本地导入,在require文件中删除pycurl。
再执行:pip install -r requirements.txt
环境准备成功。
can not import deeplearning.mplstyle in Supervised learning, like in C1_W1_Lab04_Cost_function_Soln(even more)
I just download the files from github (thank "kaieye" BTW), but it is so upset when I find I cann't run the first part of the practical. It is not the only practical lab when this things happened, so I think I must did something wrong. I tried to delete ./ , but it only work in C1_W1_lab03. Here is the situation and errors.
I do put the files of week4 in one file flod(it is not wrong, right?)
I use windows system, and my python's version is 3.11.2.
please give me some advise! I don't want give up because of this!
为啥我的训练损失值不对呢
请问一下,为啥我的训练损失值不对呢,越来越大,是不是哪里有问题
/**
* @param {[xi:number,yi:number][]} dataArr
*/
function start(dataArr) {
//线性函数模板
const yFn = (w,b,x) => w * x + b
// 样本数量
const m = dataArr.length
/**
* 损失函数 J
* @param {number} w
* @param {number} b
*/
const J = (w,b) => dataArr.reduce((t,[xi,yi]) => t + (yFn(w,b,xi) - yi) ** 2,0) / (m * 2)
// 获取 w,b关于 损失函数J的 导数
const get_dj_wb = (w,b) => dataArr.reduce((t,[xi,yi],i) => {
t.dj_dw += (yFn(w,b,xi) - yi) * xi
t.dj_db += (yFn(w,b,xi) - yi)
if (i + 1 === m) {
t.dj_dw /= m
t.dj_db /= m
}
return t
},{ dj_dw: 0,dj_db: 0 })
//初始参数 w ,b
let w = 0,b = 0
// 学习率
let L = 0.01
//开始训练
for (let i = 0; i < 10; i++) {
let sun_shi = J(w,b)
console.log('sun_shi',sun_shi)
console.log('w',w)
console.log('b',b)
let { dj_dw,dj_db } = get_dj_wb(w,b)
w = w - L * dj_dw
b = b - L * dj_db
}
}
本次课程的TensorFlow的版本应该是多少?
我使用2.4的版本,运行C2_W2_Lab02报错AttributeError: module 'tensorflow.keras.layers' has no attribute 'Normalization',升级版本到2.6又继续报这个
cannot import name 'dtensor' from 'tensorflow.compat.v2.experimental' `错误。正确的TensorFlow版本应该是多少,requirement.txt里面也没有。
How can i install lab_utils_uni.py file
I don't know how get this file.
lab_utils_common.py是什么呢?
不知道如何运行他,直接复制粘贴报错缺少东西。
这是什么程序呢?看着不像是课程里的线性回归程序呀
Advanced Learning Algorithms\week1\8号文件夹名应该加个Practice quiz
jupyter book执行lab报错No module named ‘ipympl‘
代码文件不全
如题,比如Advanced Learning Algorithms的week3,在coursera网站的每个子类里面也有实验室,但是这里没有。
https://www.coursera.org/learn/advanced-learning-algorithms/exam/bURi8/practice-quiz-advice-for-applying-machine-learning
java script error in juypter
you may find a java script error in when plot, try this
Then I purged the pip3 cache pip3 cache purge
.
Reinstall with pip3 install jupyterlab
,
then pip3 install matplotlib, pip3 install matplotlib, pip3 install ipywidgets, pip3 install ipympl.
更新最新课件
Display(visible=0, size=(840, 480)).start(); 报错
在Deep Q-Learning - Lunar Lander中,运行 Display(visible=0, size=(840, 480)).start();
报错误: hp, ht, pid, tid = _winapi.CreateProcess(executable, args,
FileNotFoundError: [WinError 2] 系统找不到指定的文件。
???
Advanced Learning Algorithms - C2_W1_Assignment issue
# UNIT TESTS
from public_tests import *
test_c1(model)
with this log
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
<ipython-input-9-c43f6ee12586> in <module>
2 from public_tests import *
3
----> 4 test_c1(model)
~/work/public_tests.py in test_c1(target)
7 def test_c1(target):
8 assert len(target.layers) == 3, \
----> 9 f"Wrong number of layers. Expected 3 but got {len(target.layers)}"
10 assert target.input.shape.as_list() == [None, 400], \
11 f"Wrong input shape. Expected [None, 400] but got {target.input.shape.as_list()}"
AssertionError: Wrong number of layers. Expected 3 but got 0
Recommend to replace "==" with ">=" in requirements.txt.
运行lab,报错“Error displaying widget”
求视频的脚本
首先感谢大佬造福人类!!
但是本蒟蒻英语渣渣,看英文字幕慢,视频自带的翻译又一般。
问一下,作者大佬能不能整理把视频的英文字幕整理成文档?本蒟蒻对着文档和ppt学可能会高效一些。
先膜为敬Orz
What should I do?
pip install -r requirements.txt出错
C2_W2_Assignment - advanced-learning-algorithms issued
z = np.array([1., 2., 3., 4.])
a = my_softmax(z)
atf = tf.nn.softmax(z)
print(f"my_softmax(z): {a}")
print(f"tensorflow softmax(z): {atf}")
# BEGIN UNIT TEST
test_my_softmax(my_softmax)
# END UNIT TEST
with this error
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-4-9cac3ae3f00f> in <module>
1 z = np.array([1., 2., 3., 4.])
----> 2 a = my_softmax(z)
3 atf = tf.nn.softmax(z)
4 print(f"my_softmax(z): {a}")
5 print(f"tensorflow softmax(z): {atf}")
<ipython-input-3-666c0ba803d5> in my_softmax(z)
12
13 ### END CODE HERE ###
---> 14 return a
NameError: name 'a' is not defined
when you upload latest course?
for downloading the slides about the missing parts in Course Two-The Advanced Algorithm
you can download the slides about the second course-the advanced learning algorithm -from the official resource,i paste the link below,hope this may help you~
https://community.deeplearning.ai/t/mls-course-2-lecture-notes/149431
C2_W1.pdf
C2_W2.pdf
C2_W3.pdf
C2_W4.pdf
Can you provide all the slides?
Can you provide all the slides, which are not available since week3 of Advanced Learning Algorithms?
pip install -r requirements.txt 报错
Folder name is not friendly to windows system, could you remove ':'
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.