### 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…

### 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…

### 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…

### 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…

### 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…

### 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…

### What is a collaborative robot used for?

In this short answer, we answer the question about what a collaborative robot is asked by one of our beloved followers. For a long time, industrial robots, which were primarily programmable robotic arms, were put in a cage separated from human workers because they were not safe to be used in proximity of humans. They were mainly used to conduct dangerous tasks unsafe for human workers. For a long time, industrial robots were put in a cage separated from human workers. Fast forward several decades, with the rise of the Internet of Things (IoT), Machine Learning (ML), advanced sensors, and…

### Robot Grasping in a Heavily Cluttered Environment

Korea Advanced Institute of Science and Technology (KAIST) student Dongwon Son has recently published interesting research about reactive grasping in a heavily cluttered environment in IEEE Robotics and Automation Letters. Reactive robot grasping in a Heavily cluttered environment. Courtesy of Samsung Research and Dongwon Son. This study proposed a closed-loop framework for predicting the six-degree-of-freedom (dof) grasp in a heavily cluttered environment using vision observations. prediction results in robot grasping. Courtesy of Samsung Research and Dongwon Son. Experimental results on a robot in an environment with a lot of clutter showed that the grasping success rate had improved quantitatively compared…

### Vector Home Robot

Vector from Digital Dream Labs (DDL) is a home robot that can tell you the weather, time your dinner, take photos, react to your touch, or even carry you to bed. Actually, not really. The last part was a joke. Vector home robot Through different embedded sensors, Vector explores and interacts with its environment, recognizes objects, and avoids obstacles. Thanks to the Vision Intelligence 200 Platform's powerful image processing and machine learning, the Vector can navigate autonomously and detect objects and sounds. There are also touch sensors, four microphones arranged in an array to detect sounds and recognize natural speech,…

### Automatic Feeding Robot

An NSF-funded project to help mitigate the problems of people with decreased mobility, especially with eating, is being conducted under the supervision of Tapomayukh Bhattacharjee at Cornell University. Image credit: Cornell University As a result of human-in-the-loop manipulation, the robot's control algorithms learn from human feedback in order to perform complex tasks related to eating. Image credit: Cornell University People who suffer from spinal cord injuries or people with limited mobility due to stroke could benefit from this research by being able to independently perform Activities of Daily Living (ADL). Watch a short video of this below: More information:https://news.cornell.edu/stories/2022/01/robot-assisted-feeding-focus-15m-nsf-grant If…