Detecting Objects using YOLOThis post deals with my small project on YOLO. It is a great project which if linked with an Arduino will certainly make you win Google Science Fair. Pardon đ It also enables to localize the object. If you lost your specs then maybe this will certainly work. So YOLO stands forContinue reading "Detecting Objects using Machine Learning I"
Build a Neural Network Classifier in 5 minutes
Hola Amigos,I actually faced a lot of issues while building my own classifier to build my own neural network classifier. Step - by - Step explanations are hardly available coz everyone here thinks that we already know 30% approx about the subject but what about a beginner? Let's face it it's very difficult to understand theseContinue reading "Build a Neural Network Classifier in 5 minutes"
Convolutional Neural Networks IV
In this post, I will deal with back propagation, gradient descent etc. Do check out my previous posts regarding Max Pooling, filters, dropout layers, fully connected layers and CNN. To begin click here.SoWhat is Back Propagation?Backpropagation is done whenever we find some error. After obtaining the probabilities of the images the CNN subtracts the actual answerContinue reading "Convolutional Neural Networks IV"
Convolutional Neural Networks III
In this post, I'll deal with dense layer, fully connected layer and backpropagation. If you have missed my previous post click here.Before moving further, let us have a view on the filter's working on an image. I made a pixelated image of the letter 'R' and applied a 3 X 3 filter one time and 3Continue reading "Convolutional Neural Networks III"
Convolutional Neural Networks II
This is my second post in CNN regarding max pooling, strides and padding.In the previous post we extracted the features from the image of '3'. Although the dimensions of the image were 4 X 24 which is quite small. But what to do when the size of the image is big having a very high resolution. GreaterContinue reading "Convolutional Neural Networks II"
Convolutional Neural Networks I
Every time I imagine CNN something spills out from my brain and forces me to restart my learning. I guess it was because I wasn't doing practicals on CNN. Many guys basically look on CNN as a theory and that is where even I lost my way of learning. However, Coursera, Edx, and Udacity helpedContinue reading "Convolutional Neural Networks I"
Deep Reinforcement Learning -Write an AI to play Pong with Q learning
In this post, we will implement Q learning to play Pong.By the end of this post, you will be able toDesign your own game in Python Pygame library. Learn the basics of Q learningImplement an efficient Policy for the agentImportantTo follow this tutorial it is highly recommended to have even a little bit of experience inPythonBackpropagation LinearContinue reading "Deep Reinforcement Learning -Write an AI to play Pong with Q learning"
Verilog Code for VGA Interface
Verilog Code for VGA InterfaceVGA (Video Graphics Array) is a connection protocol used for display related activities and actions. It is basically the connection of cables to an output device. VGA are getting replaced by HDMI and micro HDMI cables but are still in use. A VGA connector pin has 15 connection pins. There areContinue reading "Verilog Code for VGA Interface"
FPGA Simulation with Xilinx
How to simulate with FPGATo simulate your Verilog code you will need a FPGA. This tutorial willonly cover about simulating your program.Here are the things to gather up.FPGA Board USB CableXilinix ISim 14.2 or any versionBurner Software from your respective FPGA BrandWe are using here Diligent Basys2 FPGA and the software for its burning processContinue reading "FPGA Simulation with Xilinx"
Deep Copy and Shallow Copy
System Verilog Shallow Copy and Deep CopyShallow CopyWhenever we create a variable for instantiating a class a name is created and then when new command is called then an object gets created. However assigning a new handle name with a prior handle will point to the same handle until new command has been executed.Example ParentContinue reading "Deep Copy and Shallow Copy"
Shashi's Blog!! 