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 Hello! Welcome back to our tutorial. Today we will learn how to create array in tensorflow. What is tensorflow? Tensorflow is open source platform for machine learning. It has comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-art in ML and developing easily build and deploy ML powered applications.   How to import Tensorflow?    import tensorflow as tf import numpy as np  How to create array in tensorflow? We have 2 methods to create array in tensorflow:-  Using tensorflow inbuilt function Using numpy Let us understand it one by one. 1. Using Tensorflow's inbuilt function  We can create array in tensorflow using  tensorflow's inbuilt function i.e. constant arr  = tf.constant([1,2,3,4,5]) Let us understand by code:- What is constant? constant is useful for asserting that the value can be embedded that way. If the argument dtype is not specified, then the type is inferred from the type of value 2. Using Nump

  In the last post, we learned about reshaping the Numpy array. In this post, we will learn about the transpose of nd-array. Another very interesting reshaping method of Numpy is the   Transpose()   method.   Transpose is an very important topic when we talk about matrices and arrays. In linear algebra, the transpose of a matrix is an operator which flips a matrix over its diagonal. i.e.  It takes the input Array and swaps the rows and columns value and vica-versa. After transpose rows becomes columns and columns becomes rows.  Let us understand by code:-   Output:- It will convert rows into columns and columns to rows. I hope you will Like this post :) if you want to learn python then this tutorial will help you alot Python tutorial for beginners in hindi Please Subscribe to our Youtube Channel - Codin India

Hello Friends, in this tutorial we will learn about what is indexing and slicing. Let us see one by one. What is indexing? Indexing is a term of defining something orderly. It is used when we want something in a specific range. Suppose you have multiple copies of the same item and you have to remember or recognize every item then you will give every item a unique name or number. That exactly what indexing is. In   Numpy Arrays   indexing start from 0 like   List   in   Python. EX:- myarr = np.array([101,102,103,104,105]) In the given example, the indexing start from zero. If I call the 3rd item from   myarr   array it will give me 104 from the array. What is slicing of array? Slicing of arrays indicates that calling the specific value or range of value from Array. Slicing of Array is almost the same as Slicing of string. We can fetch a specific value from the array, range of values from arrays, call values in reverse order and call value by jumping one or more element. You can slice ac

    Numpy is Python module that is used for array creation, modification and creating sub arrays for numpy arrays. Concatenation of arrays Concatenation or joining of two arrays in Numpy, is primarily accomplished through the routines np.concatenate, np.vstack and np.hstack. Let us see all of the one by one. Concatenate:- It will concatenate two arrays and gives the output as one array. Let us see by code:- From the above code, it is clear that np.concatenate takes two argument as input and adds the value of both array and return the output as one array. Concatenate 3 or more arrays:- we can concatenate as any array we want. Let us talk, where the case of 3 arrays, we will concatenate all the 3 arrays Concatenation of same array:- We can also concatenate same array together. Like we can concatenate x + x. Let's see the Code:- NOTE:-   point here to be noted that, the arguments should be passed in [] brackets only.  np.concatenate([x, y]) 2-D or multidimensional Array Concatenation:

    Hey Friends, In this post we will learn about data science and career in   data science . Let us start with the definition Data Science Data Science is a field of study that combines domain expertise, programming skills and knowledge of mathematics and statistics to extract meaningful insights from data. Data:-  Data is an unorganized collection of raw materials that are collected through observations.  Data  can be text, numbers, and strings.  How data is collected? Data is collected using cookies, when you fill out any form, when you hit the like button to something and some many others way. How collected Data is useful? Collected Data is useful in many ways. Like If you ever noticed that Youtube, Google, Amazon, and many others store your activity in the form of Data.  EX:-  you If you watched a video then Youtube will recommend you the same concepts. If you search for something on Google, then Google will show you the same stuff, Amazon uses the same algorithm if you search for