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Oh Lord! Bestow me with Knowledge

Md Mahedi Hasan Mahedi-61

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Oh Lord! Bestow me with Knowledge
  • West Virginia University
  • Morgantown, WV
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@mvoelk
mvoelk / resnet-152_keras.py
Last active March 11, 2022 08:06
Resnet-152 pre-trained model in TF Keras 2.x
# -*- coding: utf-8 -*-
import cv2
import numpy as np
from tensorflow.keras.layers import Input, Dense, Conv2D, MaxPool2D, AvgPool2D, Activation
from tensorflow.keras.layers import Layer, BatchNormalization, ZeroPadding2D, Flatten, add
from tensorflow.keras.optimizers import SGD
from tensorflow.keras.models import Model
from tensorflow.keras import initializers
"""Downsized version of Xception, without residual connections.
"""
from __future__ import print_function
from __future__ import absolute_import
from keras.models import Model
from keras.layers import Dense
from keras.layers import Input
from keras.layers import BatchNormalization
from keras.layers import Activation
@stuaxo
stuaxo / fix-desktop-launcher.sh
Last active February 6, 2019 21:25
Launch desktop files instead of opening them in gedit.
$ sudo apt-get install dex
$ /usr/bin/dex -c /usr/bin/dex -t ~/.local/share/applications/

FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.


Effective Engineer - Notes

What's an Effective Engineer?

@kdkorthauer
kdkorthauer / RstudioServerSetup.sh
Created October 7, 2016 15:04
Bash script to set up R, install a few R packages, and get Rstudio Server running on ubuntu.
sudo sh -c 'echo "deb http://cran.rstudio.com/bin/linux/ubuntu trusty/" >> /etc/apt/sources.list'
gpg --keyserver keyserver.ubuntu.com --recv-key E084DAB9
gpg -a --export E084DAB9 | sudo apt-key add -
sudo apt-get update
sudo apt-get -y install r-base libapparmor1 libcurl4-gnutls-dev libxml2-dev libssl-dev gdebi-core
sudo apt-get install libcairo2-dev
sudo apt-get install libxt-dev
sudo apt-get install git-core
sudo /bin/dd if=/dev/zero of=/var/swap.1 bs=1M count=1024
from keras.models import Sequential
from keras.layers import Dense
x, y = ...
x_val, y_val = ...
# 1-dimensional MSE linear regression in Keras
model = Sequential()
model.add(Dense(1, input_dim=x.shape[1]))
model.compile(optimizer='rmsprop', loss='mse')
@fchollet
fchollet / classifier_from_little_data_script_3.py
Last active July 23, 2024 16:32
Fine-tuning a Keras model. Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats
@fchollet
fchollet / classifier_from_little_data_script_2.py
Last active September 13, 2023 03:34
Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats
@fchollet
fchollet / classifier_from_little_data_script_1.py
Last active July 27, 2024 19:40
Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats
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