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Muhammad Rizwan
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  • United Arab Emirates
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Muhammad Rizwan's blog post was featured

Face Landmark Estimation Application

Face Landmark Estimation ApplicationAfter detecting a face in an image, as seen in the earlier post ‘Face Detection Application’, we will perform face landmark estimation. Face landmark estimation means identifying key points on a face, such as the tip of the nose and the center of the eye.There are different estimation models based on the number of face landmark points. The 5 points model is the…See More
Nov 10
Muhammad Rizwan posted a blog post

Keras Application for Pre-trained Model

In earlier posts, we learned about classic convolutional neural network (CNN) architectures (LeNet-5, AlexNet, VGG16, and…See More
Nov 4
Muhammad Rizwan's blog post was featured

Keras Application for Pre-trained Model

In earlier posts, we learned about classic convolutional neural network (CNN) architectures (LeNet-5, AlexNet, VGG16, and…See More
Nov 4
Muhammad Rizwan posted a blog post

AlexNet Implementation Using Keras

Introduction:Alex Krizhevsky, Geoffrey Hinton and Ilya Sutskever created a neural network architecture called ‘AlexNet’ and won Image Classification Challenge (ILSVRC) in 2012. They trained their network on 1.2 million high-resolution images into 1000 different classes with 60 million parameters and 650,000 neurons.…See More
Oct 25
Muhammad Rizwan's blog post was featured

AlexNet Implementation Using Keras

Introduction:Alex Krizhevsky, Geoffrey Hinton and Ilya Sutskever created a neural network architecture called ‘AlexNet’ and won Image Classification Challenge (ILSVRC) in 2012. They trained their network on 1.2 million high-resolution images into 1000 different classes with 60 million parameters and 650,000 neurons.…See More
Oct 25
Muhammad Rizwan posted a blog post

LeNet-5 - A Classic CNN Architecture

Yann LeCun, Leon Bottou, Yosuha Bengio and Patrick Haffner proposed a neural network architecture for handwritten and machine-printed character recognition in 1990’s which they called LeNet-5. The architecture is straightforward and simple to understand that’s why it is mostly used as a first step for teaching Convolutional Neural Network.LeNet-5 ArchitectureOriginal image published in [LeCun et…See More
Oct 18
Muhammad Rizwan's blog post was featured

LeNet-5 - A Classic CNN Architecture

Yann LeCun, Leon Bottou, Yosuha Bengio and Patrick Haffner proposed a neural network architecture for handwritten and machine-printed character recognition in 1990’s which they called LeNet-5. The architecture is straightforward and simple to understand that’s why it is mostly used as a first step for teaching Convolutional Neural Network.LeNet-5 ArchitectureOriginal image published in [LeCun et…See More
Oct 18
Muhammad Rizwan posted a blog post

Why Use Framework for Deep Learning?

Why Use Framework for Deep Learning?You can implement your own deep learning algorithms from scratch using Python or any other programming language. When you start implementing more complex models such as Convolutional Neural Network (CNN) or Recurring Neural Network (RNN) then you will realize that it is not practical to implement very large models from scratch. There are many deep learning frameworks available in the market that makes it easy for you to implement neural networks. Some of…See More
Oct 4
Muhammad Rizwan's blog post was featured

Why Use Framework for Deep Learning?

Why Use Framework for Deep Learning?You can implement your own deep learning algorithms from scratch using Python or any other programming language. When you start implementing more complex models such as Convolutional Neural Network (CNN) or Recurring Neural Network (RNN) then you will realize that it is not practical to implement very large models from scratch. There are many deep learning frameworks available in the market that makes it easy for you to implement neural networks. Some of…See More
Oct 4
Prabhakaran Sampath liked Muhammad Rizwan's blog post K Means Clustering Algorithm & its Application
Oct 1
Prabhakaran Sampath liked Muhammad Rizwan's blog post Convolutional Neural Network  (CNN) From Scratch
Oct 1
Amit Dubey liked Muhammad Rizwan's blog post K Means Clustering Algorithm & its Application
Sep 30
Muhammad Rizwan posted a blog post

K Means Clustering Algorithm & its Application

What is K Means Clustering?Clustering means grouping things which are similar or have features in common and so is the purpose of k-means clustering. K-means clustering is an unsupervised machine learning algorithm for clustering ‘n’ observations into ‘k’ clusters where k is predefined or user-defined constant. The main idea is to define k centroids, one for each cluster.The K Means algorithm involves:Choosing the number of clusters “k”.Randomly assign each point to a cluster.Until clusters…See More
Sep 27
Muhammad Rizwan's blog post was featured

K Means Clustering Algorithm & its Application

What is K Means Clustering?Clustering means grouping things which are similar or have features in common and so is the purpose of k-means clustering. K-means clustering is an unsupervised machine learning algorithm for clustering ‘n’ observations into ‘k’ clusters where k is predefined or user-defined constant. The main idea is to define k centroids, one for each cluster.The K Means algorithm involves:Choosing the number of clusters “k”.Randomly assign each point to a cluster.Until clusters…See More
Sep 27
Muhammad Rizwan posted a blog post

Convolutional Neural Network  (CNN) From Scratch

IntroductionIn a regular neural network, the input is transformed through a series of hidden layers having multiple neurons. Each neuron is connected to all the neurons in the previous and the following layers. This arrangement is called a fully connected layer and the last layer is the output layer. In Computer Vision applications where the input is an image, we use convolutional neural network because the regular fully connected neural networks don’t work well. This is because if each pixel…See More
Sep 25
Muhammad Rizwan's blog post was featured

Convolutional Neural Network  (CNN) From Scratch

IntroductionIn a regular neural network, the input is transformed through a series of hidden layers having multiple neurons. Each neuron is connected to all the neurons in the previous and the following layers. This arrangement is called a fully connected layer and the last layer is the output layer. In Computer Vision applications where the input is an image, we use convolutional neural network because the regular fully connected neural networks don’t work well. This is because if each pixel…See More
Sep 25

Profile Information

Short Bio
I am a professional engineer, enthusiast programmer, passionate data scientist and machine learning student.

Contact: [email protected]
My Web Site Or LinkedIn Profile
http://engmrk.com
Field of Expertise
Data Science, Machine Learning, Deep Learning
Professional Status
Technical
Years of Experience:
8
Your Company:
DEWA
Your Job Title:
Engineer
How did you find out about DataScienceCentral?
internet
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Networking

Muhammad Rizwan's Blog

Face Landmark Estimation Application

Posted on November 9, 2018 at 11:19am 0 Comments

Face Landmark Estimation Application

After detecting a face in an image, as seen in the earlier post ‘Face Detection Application’, we will perform face landmark estimation. Face landmark estimation means identifying key points on a face, such as the tip of the nose and the center of the eye.…

Continue

Keras Application for Pre-trained Model

Posted on November 2, 2018 at 3:17am 0 Comments

In earlier posts, we learned about classic convolutional neural network (CNN) architectures (LeNet-5, AlexNet,…

Continue

AlexNet Implementation Using Keras

Posted on October 18, 2018 at 10:19am 0 Comments

Introduction:

Alex Krizhevsky, Geoffrey Hinton and Ilya Sutskever created a neural network architecture called ‘AlexNet’ and won Image Classification Challenge (ILSVRC) in 2012. They…

Continue

LeNet-5 - A Classic CNN Architecture

Posted on October 16, 2018 at 4:33pm 0 Comments

Yann LeCun, Leon Bottou, Yosuha Bengio and Patrick Haffner proposed a neural network architecture for handwritten and machine-printed character recognition in 1990’s which they called LeNet-5. The architecture is straightforward and simple to understand that’s why it is mostly used as a first step for teaching Convolutional Neural…

Continue

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