Neural Network Architecture in Machine Learning

Neural Network Architecture in Machine Learning

In the previous lesson, we understood how logistic regression works and how we can implement it. In the previous lesson, we used logistic regression for the binary classification of dogs based on previously seen and learned data In this lesson, we will learn about the neural network architecture in machine learning and understand the building blocks of a neural network, be introduced to different activation functions, understand the difference between shallow and deep neural networks, and become ready to use our software tools to develop a neural network. This lesson will teach us about neural network architecture in Machine Learning…
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Classification in Machine Learning Example Using Logistic Regression

Classification in Machine Learning Example Using Logistic Regression

In the previous lesson, we learned about the theory behind binary classification and logistic regression for machine learning. We learned how to classify an object based on some training examples learned before. In this lesson, we will understand how logistic regression works and how we can implement it. In other words, we will see a classification in machine learning example using logistic regression. In this lesson, we want to use logistic regression for the binary classification of dogs based on previously seen and learned data Watch the video version of the 7th lesson: Download the Python code at the link…
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Binary Classification and Logistic Regression in Machine Learning

Binary Classification and Logistic Regression in Machine Learning

In the previous lesson, we solved an example of linear regression for machine learning. We used linear regression to solve a stereo vision depth estimation problem for an Autonomous underwater vehicle (AUV). We also implemented vectorization using Python. a stereo vision depth estimation problem for an AUV The purpose of this lesson is to introduce binary classification and logistic regression for machine learning. We will learn how to classify an object based on some training examples learned before. We will implement this in Python in the next lesson. Watch the video version of the 6th lesson: What application did the…
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Linear Regression for Machine Learning: an Example

Linear Regression for Machine Learning: an Example

In the previous lesson, we learned about linear regression in machine learning (ML). We understood the basic theory behind linear regression, and we got ready to implement linear regression in a real-life situation using Python in this lesson. We also used an algorithm called Gradient Descent which is an optimization algorithm to find the minimum of a function. Machine learning begins with the most straightforward and basic concept, linear regression in machine learning. Please read the following lesson first if you are not familiar with linear regression in machine learning: https://www.mecharithm.com/linear-regression-for-machine-learning/ This lesson is about the linear regression machine learning…
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Linear Regression for Machine Learning

Linear Regression for Machine Learning

In the previous lessons from the series of lessons on Machine Learning (ML) in robotics, we learned how to set up our project environment and how to code in an IDE using the Python language. This lesson is about linear regression in machine learning (ML). We will understand the basic theory behind linear regression, and we will get ready to implement linear regression in a real-life situation using Python in our next lesson. We will also use an algorithm called Gradient Descent which is an optimization algorithm to find the minimum of a function. Machine learning begins with the most…
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Python for Machine Learning in 40 Minutes

Python for Machine Learning in 40 Minutes

Up to this point, we got a clear understanding of the importance of Machine Learning in Robotics. Additionally, we learned how to use Ubuntu, install software utilities, and set up virtual environments. Here we will have a crash course on Python for our Machine Learning tutorials so that a lack of Python knowledge will not hinder you. The purpose of this lesson is to teach you how to use Spyder IDE for writing Python code. You will be introduced to variables, strings, lists, loops, if statements, and Numpy, which is very important for matrix and vector operations that are essential…
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Guns (Utilities) Needed for Following Machine Learning Tutorials

Guns (Utilities) Needed for Following Machine Learning Tutorials

You need guns (software & hardware), lots of guns, to smoothly follow the machine learning tutorials. From the movie "Matrix" In this lesson, you will get a brief introduction to virtual environments, what they are and why we need them. We need virtual environments for our machine learning tutorials Following that, you'll learn about IDEs (Integrated Development Environments) and then get a brief overview of Ubuntu. The next step is the installation of Anaconda and the creation of virtual environments. Finally, you will install Tensorflow, which you will need later on in the machine learning tutorials. IDE or Integrated Development…
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the Sapien 6M Intelligent Robotic Arm

the Sapien 6M Intelligent Robotic Arm

Sapien 6M is an intelligent robotic arm from Sarcos Robotics that can lift more than its own weight! Yes, it has a very good strength-to-weight ratio. the Sapien 6M Intelligent Robotic Arm from Sarcos Robotics Enhanced for autonomous mobile manipulation, the 44 kg/97 lb intelligent robotic arm is capable of lifting payloads up to 50 kg/110 lb. As you can see in the video below, it can lift an 80-lb dumbbell with ease. The Sapien 6M robotic arm can be mounted on an autonomous mobile platform for mobile manipulation. Everything is embedded in the intelligent robotic arm, and no external…
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Introduction to Machine Learning (ML)

Introduction to Machine Learning (ML)

Welcome to the desert of the real. We are excited to announce that following the requests from our Mecharithm family to design a Machine Learning (ML) course, especially for roboticists, we are now able to provide you with a machine learning course specifically designed for robotics applications.  Here are the contents of the whole course on machine learning for robotics: Quick crash course on Python The linear regression problem + small application The logistic regression problem + application on image classification Introduction to supervised learning: Neural networks 1 Introduction to supervised learning: Neural networks 2 Introduction to supervised learning: Neural…
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Forward Kinematics in Robotics Using Screw Theory

Forward Kinematics in Robotics Using Screw Theory

Can you recall a time when you were frustrated when attempting to compute the forward kinematics for robotic systems? Did you find it frustrating to assign coordinate frames to each link when robots become more sophisticated?  The frustration caused by assigning coordinate frames for each link while solving the forward kinematics of robotic systems using methods like Denavit-Hartenberg is REAL. If your answer to these questions is yes, and you're tired of cumbersome methods like Denavit-Hartenberg to calculate the forward kinematics of robotic chains, this lesson is for you.  The Denavit-Hartenberg is one of the methods to derive the forward…
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