├── project_code2.py ├── project_code3.py ├── project_code1.py ├── Project_code2.ipynb ├── Project_Code3.ipynb ├── README.md └── Project_code1.ipynb /project_code2.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """Project_code2.ipynb 3 | 4 | Automatically generated by Colaboratory. 5 | 6 | Original file is located at 7 | https://colab.research.google.com/drive/1y2AoVaFeHQepmQsbJMo6CJyqGdPU0jHE 8 | 9 | GAN 10 | """ 11 | 12 | # Commented out IPython magic to ensure Python compatibility. 13 | import tensorflow as tf 14 | import random 15 | import numpy as np 16 | import matplotlib.pyplot as plt 17 | # %matplotlib inline 18 | 19 | 20 | 21 | """For Full Project, Mail me at (vatshayan007@gmail.com) Now""" -------------------------------------------------------------------------------- /project_code3.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """Project_Code3.ipynb 3 | 4 | Automatically generated by Colaboratory. 5 | 6 | Original file is located at 7 | https://colab.research.google.com/drive/1vJBuMzL8mUg5WGnqvWpllUiG9dYZrWhM 8 | 9 | Convolution 10 | """ 11 | 12 | import keras 13 | from keras.datasets import mnist 14 | from keras.models import Sequential 15 | from keras.layers import Dense, Dropout, Flatten 16 | from keras.layers import Conv2D, MaxPooling2D 17 | import numpy as np 18 | 19 | 20 | 21 | """This is Just a Demo !""" 22 | 23 | 24 | 25 | """For Full Project, Mail me at vatshayan007@gmail.com Now""" 26 | 27 | -------------------------------------------------------------------------------- /project_code1.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """Project_code1.ipynb 3 | 4 | Automatically generated by Colaboratory. 5 | 6 | Original file is located at 7 | https://colab.research.google.com/drive/1CqZHrp9zekvC_ZU_LbAUGds6RpjRj6yT 8 | """ 9 | 10 | 11 | 12 | """## CNN Hamming 13 | 14 | """ 15 | 16 | # Commented out IPython magic to ensure Python compatibility. 17 | import numpy as np 18 | import pandas as pd 19 | import matplotlib.pyplot as plt 20 | # %matplotlib inline 21 | from keras.datasets import mnist 22 | from keras.models import NSequential 23 | from keras.layers import Dense, Dropout, Activation, Flatten 24 | from keras.optimizers import Adam 25 | from keras.layers.normalization import BatchNormalization 26 | from keras.utils import np_utils 27 | from keras.layers import Conv2D, MaxPooling2D, ZeroPadding2D, GlobalAveragePooling2D 28 | from keras.layers.advanced_activations import LeakyReLU 29 | from keras.preprocessing.image import ImageDataGenerator 30 | 31 | 32 | 33 | """This is only Small Demo. 34 | For Full Project, 35 | Mail me at (vatshayan007@gmail.com) Now! 36 | 37 | 38 | 39 | """ -------------------------------------------------------------------------------- /Project_code2.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Project_code2.ipynb", 7 | "provenance": [] 8 | }, 9 | "kernelspec": { 10 | "name": "python3", 11 | "display_name": "Python 3" 12 | } 13 | }, 14 | "cells": [ 15 | { 16 | "cell_type": "markdown", 17 | "metadata": { 18 | "id": "jajJE0CFei1I" 19 | }, 20 | "source": [ 21 | "\n", 22 | "GAN\n" 23 | ] 24 | }, 25 | { 26 | "cell_type": "code", 27 | "metadata": { 28 | "id": "VoPh4QOqenlJ" 29 | }, 30 | "source": [ 31 | "import tensorflow as tf\n", 32 | "import random\n", 33 | "import numpy as np\n", 34 | "import matplotlib.pyplot as plt\n", 35 | "%matplotlib inline" 36 | ], 37 | "execution_count": 1, 38 | "outputs": [] 39 | }, 40 | { 41 | "cell_type": "code", 42 | "metadata": { 43 | "id": "uYQWBJzWepyh" 44 | }, 45 | "source": [ 46 | "" 47 | ], 48 | "execution_count": null, 49 | "outputs": [] 50 | }, 51 | { 52 | "cell_type": "markdown", 53 | "metadata": { 54 | "id": "Ecfc8q7oeqRB" 55 | }, 56 | "source": [ 57 | "For Full Project, Mail me at (vatshayan007@gmail.com) Now" 58 | ] 59 | } 60 | ] 61 | } -------------------------------------------------------------------------------- /Project_Code3.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Project_Code3.ipynb", 7 | "provenance": [] 8 | }, 9 | "kernelspec": { 10 | "name": "python3", 11 | "display_name": "Python 3" 12 | } 13 | }, 14 | "cells": [ 15 | { 16 | "cell_type": "markdown", 17 | "metadata": { 18 | "id": "y8tk7yUqfyJo" 19 | }, 20 | "source": [ 21 | "Convolution" 22 | ] 23 | }, 24 | { 25 | "cell_type": "code", 26 | "metadata": { 27 | "id": "7hmRrahPf0PI" 28 | }, 29 | "source": [ 30 | "import keras\n", 31 | "from keras.datasets import mnist\n", 32 | "from keras.models import Sequential\n", 33 | "from keras.layers import Dense, Dropout, Flatten\n", 34 | "from keras.layers import Conv2D, MaxPooling2D\n", 35 | "import numpy as np" 36 | ], 37 | "execution_count": 1, 38 | "outputs": [] 39 | }, 40 | { 41 | "cell_type": "code", 42 | "metadata": { 43 | "id": "Fl3jjLfwf6Hc" 44 | }, 45 | "source": [ 46 | "" 47 | ], 48 | "execution_count": null, 49 | "outputs": [] 50 | }, 51 | { 52 | "cell_type": "markdown", 53 | "metadata": { 54 | "id": "5pA7CxKYf8I6" 55 | }, 56 | "source": [ 57 | "This is Just a Demo !" 58 | ] 59 | }, 60 | { 61 | "cell_type": "code", 62 | "metadata": { 63 | "id": "5DINs1lkf_VG" 64 | }, 65 | "source": [ 66 | "" 67 | ], 68 | "execution_count": null, 69 | "outputs": [] 70 | }, 71 | { 72 | "cell_type": "markdown", 73 | "metadata": { 74 | "id": "laTEb4Auf_1m" 75 | }, 76 | "source": [ 77 | "For Full Project, Mail me at vatshayan007@gmail.com Now" 78 | ] 79 | }, 80 | { 81 | "cell_type": "code", 82 | "metadata": { 83 | "id": "R4In0jA0gG81" 84 | }, 85 | "source": [ 86 | "" 87 | ], 88 | "execution_count": null, 89 | "outputs": [] 90 | } 91 | ] 92 | } -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Cryptography-and-Neural-Network-Project 2 | 3 | ![Disease Prediction using Machine Learning](https://user-images.githubusercontent.com/28294942/209939755-13c89962-118b-45d5-9744-f502802b6403.png) 4 | 5 | ## DISTINGUISHING RANDOM BITSTREAM FROM HAMMING ENCODED BITSTREAM 6 | 7 | ### My internship was carried out at Defence Research and Development Organization(DRDO), New Delhi. My area of work was Deep Neural Networks and Cryptography. 8 | 9 | Deep learning is part of a broader family of machine learning methods based on artificial neural networks. Learning can be supervised, semi-supervised or unsupervised. Deep neural networks are the networks that have an input layer, an output layer and at least one hidden layer in between. Each layer performs specific types of sorting and ordering in a process that some refer to as “feature hierarchy.” One of the key uses of these sophisticated neural networks is dealing with unlabeled or unstructured data. 10 | 11 | Cryptography is the art of creating written or generated codes that allow information to be kept secret. Cryptography converts data into a format that is unreadable for an unauthorized user, allowing it to be transmitted without unauthorized entities decoding it back into a readable format, thus compromising the data. Information security uses cryptography on several levels. The information cannot be read without a key to decrypt it. 12 | 13 | There are various types of concepts and libraries we studied about, some common concepts and libraries include: Tensorflow, Keras, RNN, CNN, LSTM, GRU, Sequential, Max pooling, Dense, etc 14 | 15 | ________________________________________________________________________________________________________________________________________________________________________________ 16 | 17 | ### Need Code, Documents & Explanation video ? 18 | 19 | ## How to Reach me : 20 | 21 | ### Mail : vatshayan007@gmail.com 22 | 23 | ### WhatsApp: **+91 9310631437** (Helping 24*7) **[CHAT](https://wa.me/message/CHWN2AHCPMAZK1)** 24 | 25 | ### Website : https://www.finalproject.in/ 26 | 27 | ### 1000 Computer Science Projects : https://www.computer-science-project.in/ 28 | 29 | Mail/Message me for Projects Help 🙏🏻 30 | -------------------------------------------------------------------------------- /Project_code1.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Project_code1.ipynb", 7 | "provenance": [] 8 | }, 9 | "kernelspec": { 10 | "name": "python3", 11 | "display_name": "Python 3" 12 | } 13 | }, 14 | "cells": [ 15 | { 16 | "cell_type": "code", 17 | "metadata": { 18 | "id": "ZVlCV1dLc1OT" 19 | }, 20 | "source": [ 21 | "" 22 | ], 23 | "execution_count": null, 24 | "outputs": [] 25 | }, 26 | { 27 | "cell_type": "markdown", 28 | "metadata": { 29 | "id": "IpiYL1Hoc9XR" 30 | }, 31 | "source": [ 32 | "## CNN Hamming \n" 33 | ] 34 | }, 35 | { 36 | "cell_type": "code", 37 | "metadata": { 38 | "id": "ssgga8f1dAOF" 39 | }, 40 | "source": [ 41 | "import numpy as np\n", 42 | "import pandas as pd\n", 43 | "import matplotlib.pyplot as plt\n", 44 | "%matplotlib inline\n", 45 | "from keras.datasets import mnist\n", 46 | "from keras.models import NSequential\n", 47 | "from keras.layers import Dense, Dropout, Activation, Flatten\n", 48 | "from keras.optimizers import Adam\n", 49 | "from keras.layers.normalization import BatchNormalization\n", 50 | "from keras.utils import np_utils\n", 51 | "from keras.layers import Conv2D, MaxPooling2D, ZeroPadding2D, GlobalAveragePooling2D\n", 52 | "from keras.layers.advanced_activations import LeakyReLU \n", 53 | "from keras.preprocessing.image import ImageDataGenerator" 54 | ], 55 | "execution_count": 1, 56 | "outputs": [] 57 | }, 58 | { 59 | "cell_type": "code", 60 | "metadata": { 61 | "id": "eK4S3c6pdB-y" 62 | }, 63 | "source": [ 64 | "" 65 | ], 66 | "execution_count": 1, 67 | "outputs": [] 68 | }, 69 | { 70 | "cell_type": "markdown", 71 | "metadata": { 72 | "id": "ZQvhK72_dEAG" 73 | }, 74 | "source": [ 75 | "This is only Small Demo.\n", 76 | "For Full Project,\n", 77 | "Mail me at (vatshayan007@gmail.com) Now!\n", 78 | "\n", 79 | "\n" 80 | ] 81 | }, 82 | { 83 | "cell_type": "markdown", 84 | "metadata": { 85 | "id": "Rtk53BI7dWoG" 86 | }, 87 | "source": [ 88 | "" 89 | ] 90 | } 91 | ] 92 | } --------------------------------------------------------------------------------