Linear Algebra is to machine learning as flour to bakery: Every machine learning model is based on linear algebra, as every cake is base on flour (But ML model is not about only Linear algebra, they need calculus, probability, and optimization too).
Linear algebra via the use of matrices and vectors, allows us to perform a large number of calculations in a more efficient way while using simpler code with the help of linear algebra library (such as NumPy). Linear Algebra relates variables(Dependent Variables, Independent Variables, and Target Variables) by a mathematical relationship.
Vectors are ordered finite lists of numbers…
In the Machine learning process, Data Preprocessing is that step in which the data gets transformed or Encoded so that machine can easily parse it.
WHY Data Preprocessing ?
As Machines don’t understand text, image, or video data as it is, they only understand 0s and 1s. So if we put several folds of images and expect our machine learning model to get trained, IT WILL NOT HAPPEN.
In the real world, data are generally incomplete; lacking attribute values, duplicate values, or containing only aggregate data, noisy data: containing errors or outliers due to human error or false or manipulated…
It is a field of artificial intelligence that trains computers to interpret and understand the visual world. It is the process by which we can understand the images and videos how they are stored and how we can manipulate and retrieve information from them.
What problem it Solves ?
pandas is a Python package that provides a fast, flexible, and expressive data structure designed to make working with “relational” or “labeled” data easy and intuitive.
Limitation of NumPy
for performance, NumPy arrays were significantly faster but NumPy is missing features to enable data analysis on relational data(data that are related to one another). A few of the features missed in NumPy are :
Why Pandas ?
pandas are+ built on top of NumPy to make…
NumPy (Numerical Python) is an open source Python library ,a fundamental package for scientific computing in Python. Some of the features we’ll find in NumPy :
According to Arthur Samuel(1959) : Machine learning is a “Field of study that gives computers the ability to learn without being explicitly programmed.” In other words it is concerned with the question of how to construct computer programs that automatically improve with the experience.
Machine learning Categorized on the basis of Learning :
✨ Supervised learning : Machine learning that are designed to learn by examples, i.e., It maps the input to an output based on previous input-output pairs. It is trained with labelled data.
Database is a collection of information that is organized so that it can be easily accessed, managed and updated. Databases typically contain aggregations of data records or files, containing information. A database is an abstraction over an operating system’s file system that makes it easier for developers to build applications that create, read, update and delete persistent data.
Databases make structured storage reliable and fast. They also give you a framework for how the data should be saved and retrieved instead of having to figure out what to do with the data every time you build a new application.
Files are named locations on disk to store related information. Images, text, video, audio, scripts etc. are the may types of files. In Python there are 2 types of files: (i) Binary (ii) Text
Python has several functions for creating, reading, writing, updating and deleting files. Hence, in Python, a file operation takes place in the following order:
(i) Open a file
(ii) Read or write(any operation)
(iii) Close the file
file = open("samplefile.txt") # equivalent to 'r' or 'rt'
file = open("samplefile.txt",'w') # write in text mode
file = open("img.bmp",'r+b')…
Yeah ! Python is an interpreted language ( it means a computer program that translates and executes, line by line, a program written in a high level language), although compilation is a step. Python code, written in .py file is compiled to what is called bytecode and stored in .pyc format. This bytecode is a low level set of instructions that can be executed by an interpreter. The bytecode compilation happened internally, and almost completely hidden from developer. Bytecode instructions are executed on Virtual Machine.
Searching in a dictionary is way much faster than searching in a list, it is…
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