Anchit_210133_week1

w1/anacondasetup.md

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+## Basis Of Learning##
+SnT project 2022
+
+## step 1- Installing anacoda ##
+download anaconda distribution from https://www.anaconda.com/download/#windows
+install with all the packages.
+
+## conda installation ##
+Open anaconda navigator 
+In the anaconda navigator open powershell prompt there run the following commands 
+         conda -V
+it shows the version of conda installed on the windows
+
+## creating virtual environments in conda ##
+           conda create -n name_of_the_file python=3.9
+this creates a Venvironment 
+
+## to activate VEnvironment
+
+          conda activate deeplearn
+
+## to install numpy,pandas,matplotlib
+
+          conda install numpy
+          conda install pandas
+          conda install matplotlib
+
+
+## to check the version of the various libraries
+
+         print(numpy.__version__)
+         print(pandas.__version__)
+         print(matplotlib.__version__)
+
+## completed with the anaconda distribution and created environments 

w1/jupiter_guide.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "after installing anaconda open anaconda navigator and then jupyter\n",
+    "notebook\n",
+    "\n",
+    "to create a new file in the notebook click on the “new”,and then select\n",
+    "the type of the file you want to create.\n",
+    "\n",
+    "if you create a python3 kernel notebook then you need to rename it by\n",
+    "clicking onthe topmost point right of the jupyter\n",
+    "\n",
+    "type the commands in the IN box and then for execution click on “run”\n",
+    "\n",
+    "the file by default get saved in cdrive . so we have created the file\n",
+    "now code for eg. print(“BcS OP”) after the completion of the file you\n",
+    "need to save\n",
+    "\n",
+    "and we completed the jupyter setup"
+   ]
+  }
+ ],
+ "nbformat": 4,
+ "nbformat_minor": 5,
+ "metadata": {}
+}

w1/matplotlib_guide.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## install matplotlib library using conda environment\n",
+    "\n",
+    "In the python3 kerenel import matplotlib.pyplot as plt\n",
+    "\n",
+    "## plotting methods\n",
+    "\n",
+    "by plot function you create a graph and to display it show function used\n",
+    "\n",
+    "\\*\\*\\*\\*\\*\\*line graph\\*\\*\\* plt.plot(\\[1,2,3\\],\\[4,5,6\\]) plt.show()\n",
+    "\n",
+    "## attributes\n",
+    "\n",
+    "\\*\\*label function is used to create axis names\n",
+    "\n",
+    "plt.plot(\\[1,2,3\\],\\[4,5,6\\]) plt.xlabel(“jkl”) plt.ylabel(“lkj”)\n",
+    "plt.show()\n",
+    "\n",
+    "**title function is used to give graph a name **legend is used in bar\n",
+    "and histogram\n",
+    "\n",
+    "plt.title(“regression_demo”) plt.legend()\n",
+    "\n",
+    "\\*\\*\\*\\*\\*\\*bar graph label for each bar and color for different graph\n",
+    "\n",
+    "plt.bar(\\[1,2,3\\],\\[4,5,6\\],label=“pros”,color=‘g’)\n",
+    "plt.bar(\\[7,8,9\\],\\[10,5,8\\],label=“os”,color=‘k’) plt.show()\n",
+    "\n",
+    "\\*\\*linewidth is used for differing line width\n",
+    "\n",
+    "plt.bar(\\[1,2,3\\],\\[4,5,6\\],label=“pros”,color=‘g’,linewidth=10)\n",
+    "plt.bar(\\[7,8,9\\],\\[10,5,8\\],label=“os”,color=‘k’,linewidth=14)\n",
+    "plt.show()\n",
+    "\n",
+    "\\*\\*grid is used for developing a grid\n",
+    "\n",
+    "plt.bar(\\[1,2,3\\],\\[4,5,6\\],label=“pros”,color=‘g’,linewidth=10)\n",
+    "plt.bar(\\[7,8,9\\],\\[10,5,8\\],label=“os”,color=‘k’,linewidth=14)\n",
+    "plt.grid(‘true’,color=‘c’) plt.show()\n",
+    "\n",
+    "\\*\\*\\*\\*\\*\\*histogram\n",
+    "\n",
+    "bins=\\[0,10,20,30,40,50,60,70,80,90,100\\]\n",
+    "ghbc=\\[0,22,33,21,30,45,54,56,55,87,54,90,54\\]\n",
+    "plt.hist(ghbc,bins,histtype=‘bar’,color=‘r’,rwidth=0.8)\n",
+    "\n",
+    "\\*\\*\\*\\*\\*\\*scatter\n",
+    "\n",
+    "x=\\[1.2.3.4.5\\] y=\\[2,0,8,7,6\\] plt.scatter(x,y,color=‘r’) plt.show()"
+   ]
+  }
+ ],
+ "nbformat": 4,
+ "nbformat_minor": 5,
+ "metadata": {}
+}

w1/numpy_guide.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## install the numpy library in conda environment\n",
+    "\n",
+    "In the notebook python kernel import numpy as np\n",
+    "\n",
+    "## creation of numpy arrays\n",
+    "\n",
+    "a=np.array(\\[elements\\]) eg. a=np.array(\\[1,2,3,4,5\\]) print(a)\n",
+    "—\\>\\[1,2,3,4,5\\]\n",
+    "\n",
+    "you can create a 2D array or nD array eg.\n",
+    "a=np.array(\\[\\[1,2,3\\],\\[4,5,6\\]\\]) print(a) —-\\>\\[\\[1,2,3\\] \\[4,5,6\\]\\]\n",
+    "\n",
+    "## attributes of arrays\n",
+    "\n",
+    "consider a array ‘a’ a=np.array(\\[1,2,3\\])\n",
+    "\n",
+    "*dimensions* a.ndim\n",
+    "\n",
+    "*shape* //gives the no.of rows,colns a.shape\n",
+    "\n",
+    "*type * a.dtype dtype’int32’ (output here)\n",
+    "\n",
+    "*itemsize* a.itemsize 4\n",
+    "\n",
+    "*nbytes* —-\\> gives total size of the array a.nbytes 12\n",
+    "\n",
+    "*getting a specific element* a\\[0,2\\] ——\\>3\n",
+    "\n",
+    "*getting a row* a\\[0,:\\] \\[1,2,3\\]\n",
+    "\n",
+    "*creating a array full of one or zero element* b=np.ones((2,3)\n",
+    ",dtype=‘int32’) print(b) ———\\>\\[\\[1,1,1\\] \\[1,1,1\\]\\]\n",
+    "\n",
+    "*creating a array full of same element*\n",
+    "h=np.full((2,3),99,dtype=‘int32’) print(h)\n",
+    "\n",
+    "—-\\> \\[\\[99,99,99\\] \\[99,99,99\\]\\]\n",
+    "\n",
+    "*creating a identity matrix* j=np.identity(4) print(j)\n",
+    "\n",
+    "—\\> \\[\\[1,0,0,0\\] \\[0,1,0,0\\] \\[0,0,1,0\\] \\[0,0,0,1\\]\\]\n",
+    "\n",
+    "*some mathematical tool* np.cos(a) np.sin(a) a/2 a\\*\\*2 (gives all the\n",
+    "elements raised to the power 2)\n",
+    "\n",
+    "*matrix multiplication* np.matmul(a,b)"
+   ]
+  }
+ ],
+ "nbformat": 4,
+ "nbformat_minor": 5,
+ "metadata": {}
+}