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Pattern Recognition Basics.
Pattern Recognition can be defined as the classification of the data on the basis of the knowledge gained or on the basis of statistical information extracted from patterns and their representations…
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Rule Based Pattern Recognition
In this article, my purpose is to find simple rules and create a program that understands the structure of other program which is ruled based system. I create random x numbers on variable numbers and…...
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Pattern Recognition With Machine Learning
One of the most common applications of machine learning is pattern recognition. Computers that use well-trained algorithms recognize animals in photos, anomalies in stock fluctuations, and signs of…
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Feature Detection
In this tutorial you will learn how to: Theory Code C++ Java Python Explanation Result
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Handwritten Digit Recognition
The main objective is to classify the pattern into the handwritten digits provided by the MNIST data set of images. Manually written digits have an invariant position, shape, style, etc. so it…
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Handwritten Digit Recognition
Neural network is trying to process neurons and building these complex brain networks that can be trained. Specialized subset of Machine learning that uses layered neural network to simulate human…
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(Part 2) Pattern Recognition and Perceptrons
This article motivates you to study about Perceptrons. The Perceptron algorithm has been implemented in Python.
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Digit recognition
Just like in traditional programming we first learn to print "Hello, world!", similarly in machine learning we first understand the solution to recognizing the images of handwritten digits. The…
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Neural Network
Neural network are sophisticated learning algorithms used for learning complex, often a non-linear machine learning model.
Read more at Towards Data ScienceClustering, and its Methods in Unsupervised Learning
Type of Machine Learning where patterns are detected in datasets without knowing the labels is called Unsupervised Learning. Information is extracted from data by segmentation and more complex…
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The Fundamentals of Image Recognition
What is this? These are just strange symbols placed in a particular order that hold no meaning if not digested correctly, yet your mind is continuously making sense of this collection of nonsense…
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Part 1: Image Processing
We will be creating a Sudoku Solver AI using python and Open CV to read a Sudoku puzzle from an image and solving it using constraint programming. In this article we we will be using image processing ...
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Computer Vision
It has been well established and documented that the computational capabilities of computers far exceed that of human beings. Hence, since the middle of the 20th century, computation heavy activities…...
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Object Detection
Object detection, especially recognition can be done using different technics, like a combination of OpenCV functions. For me, it was rather interesting to build a quick model in R then to spend…
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Commonly used functions of Pandas data structures library
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A Basic Neural Network!!
This post consists of a Basic Neural Network Implementation using TensorFlow, Keras, Numpy, and Python. TensorFlow is a free and open-source software library for dataflow and differentiable…
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Acute lymphoblastic leukemia (ALL) Versus Machine Learning. Machine learning can diagnose ALL and lead the fight to cure cancer
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Machine Learning
This article will cover most of the important topics used in machine learning and explain their presence in each step. AI is something that scientists want to achieve, machine intelligence is a…
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Machine Learning
In computer vision, semantic segmentation is one of the most important components for fine-grained inference (CV). To achieve the appropriate precision levels, models must grasp the context of the…
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Machine learning has been one of the few buzzwords of the 21st century that are here to stay. Surprisingly enough, machine learning has been present in theory longer than we could imagine. But what…
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Machine Learning : Supervised Learning
Supervised Machine Learning , Types of Supervised Machine Learning and ML algorithms. Machine Learning | Data Science | Data Analysis | Data
Read more at Towards Data ScienceUnderstand the Patterns in the Data
In my previous blog, I explained how to clean the data, perform EDA (exploratory data analysis) and what is a basic feature engineering in brief. So let’s say, you did a “read_csv” and imported the…
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Neural Networks
In the same way that when you start programming in a new language there is a tradition of doing it with a Hello World print, in Deep Learning you start by creating a recognition model of handwritten…
Read more at Towards Data ScienceDetecting patterns and generalizing
Before the advent of modern deep learning, images and sounds were unstructured data files, there was no way computers could interpret their contents. The computer vision area was dominated by…
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