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# coding: utf-8 | |
# # Computing Regression parameters (closed form example) | |
# The data | |
# Consider the following 5 point synthetic data set | |
# In[1]: |
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# coding: utf-8 | |
# # Computing Regression parameters (gradient descent example) | |
# The data | |
# Consider the following 5 point synthetic data set | |
# In[1]: |
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upload=true&script=true&cardinfo= | |
!!################################ | |
!!ALSA Information Script v 0.4.64 | |
!!################################ | |
!!Script ran on: Wed Apr 19 15:32:56 UTC 2017 | |
!!Linux Distribution | |
!!------------------ |
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# this makefile works with system libcurl or libcurl built by | |
# me. | |
# | |
# myversion of lib curl is in : | |
#LIBCURL_DIR=/home/davis/progs/notmine/curl | |
#MYINC=${LIBCURL_DIR}/include/ | |
#MYLIB=${LIBCURL_DIR}/lib/.libs/ |
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test from R | |
T 192.168.1.4:41772 -> 107.170.47.130:80 [AP] | |
POST /post.php HTTP/1.1. | |
Host: www.posttestserver.com. | |
User-Agent: libcurl/7.52.1 r-curl/3.0 httr/1.3.1. | |
Accept-Encoding: gzip, deflate. | |
Accept: application/json, text/xml, application/xml, */*. | |
Content-Type: application/octet-stream. | |
Content-Length: 7. |
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# coding: utf-8 | |
# In[1]: | |
# Start of code for librosa walkthrough | |
# add autocomplete with TAB | |
# get_ipython().run_line_magic('config', 'IPCompleter.greedy=True') |
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Using this guide, here are my notes in that regard: | |
=================================================== | |
https://wiki.debian.org/NvidiaGraphicsDrivers/Optimus | |
lspci | grep 3D | |
02:00.0 3D controller: NVIDIA Corporation GM108M [GeForce 940MX] (rev a2) | |
My bios does not have the ability to disable the intel driver. | |
I installed x11-xserver-utils |
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Downloading and Extracting Packages | |
audioread-2.1.5 | 28 KB | ####################################### | 100% | |
certifi-2018.4.16 | 142 KB | ####################################### | 100% | |
librosa-0.6.1 | 1.5 MB | ####################################### | 100% | |
libiconv-1.15 | 2.0 MB | ####################################### | 100% | |
conda-4.5.8 | 624 KB | ####################################### | 100% | |
resampy-0.2.1 | 330 KB | ####################################### | 100% | |
x264-20180712 | 5.0 MB | ####################################### | 100% | |
ffmpeg-2.8.6 | 55.2 MB | ####################################### | 100% | |
joblib-0.12 | 167 KB | ####################################### | 100% |
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INPUT_COLUMNS = [ | |
# Define features | |
tf.feature_column.categorical_column_with_vocabulary_list('dayofweek', vocabulary_list = ['Sun', 'Mon', 'Tues', 'Wed', 'Thu', 'Fri', 'Sat']), | |
tf.feature_column.categorical_column_with_identity('hourofday', num_buckets = 24), | |
] |
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It looks like copy and paste of the tsv file replaced tabs with spaces. Here is where the original file can be found. | |
https://waterdata.usgs.gov/nwis/dv?cb_00045=on&cb_62620=on&format=rdb&site_no=0204288721&referred_module=sw&period=&begin_date=2018-04-12&end_date=2019-04-12 |