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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:

   Linked List is a linear data structure. Unlike arrays, linked list elements are not stored at a contiguous location. The element are linked using pointers. Why Linked list is used:- Arrays can be used to store linear data of similar types, but arrays have the following limitations. Array's size is fixed. So we must know the highest limit of the array in advance. So we must declare the size of the array first and elements there after.  Inserting a new element is very expensive because the room has to be be created for the new elements and shift the existing elements. Ex :- Suppose we have arrays in sorted order   i.e. [1,2,3,4,6,7]  and we have to insert new element   i.e. [5]   in the array. So in order to maintain elements in sorted order, we have to place that element after suitable element. In this situation we have to shift the element   i.e. [6,7] by position 1. Now  we saw the arrays limitations. Let's understand the advantages of the Linked List over array.  Advantage

  Data Structure   is a particular way of organizing data in a Computer, so that it can be used effectively. For Example:-   We can store a list of items having the same data-type using arrays. Data structures are fundamental concepts of computer science which helps is writing efficient programs in any language. Python is a high-level, interpreted, interactive and object-oriented scripting language using which we can study the fundamentals of data structure in a simpler way as compared to other programming languages. Types of Data Structure Data structures in computer science are divided into two categories. We will discuss about each of the below data structures in detail one by one. In today's post we will only discuss about data structure definition and its types. We will learn and implement its various types one by one with example. Data Structure Linear Data Structure Non-Linear Data Structure Linear Data Structure A Linear data structure have data elements arranged in sequent

  In the modern era, where the technology is so vast, it is not compulsory to attend the particular graduation programs for the student to master any technology. If you have that passion for programming then there are various learning methods and resources available (online and offline both) that can help you to be a  Self-Taught   Programmer or Developer. You can use thes resources to master in any technology without any Syllabus or curriculum barrier. In the journey of a   Self-Taught   Developer or Programmer, there is lots of dedication and consistency required. However, being a self-taught developer doesn't mean to not attend any Degree or to not follow any mentor but it tends that you are not dependant on any particular person or platform to master the development skills. Before moving further, let us take a look at several major benefits for being a self-taught Developer:- Self-Taught Developers are generally more proficient as they are not required to follow any particular