Datamahadev com 9 important techniques for every python beginner part 2. Datamahadev com classification algorithms explained in 30 minutes. Datamahadev com ai pilot deep reinforcement learning change aviation warfare. NumPy Reshape: 9 most important techniques for every Python beginner-Part 2 - datamahadev.com. Hi all, I hope you all are safe and sound in these times of distress and are recreating, reskilling yourself in this worldwide lockdown because of the pandemic.
In the previous part(click here for Part 1), I had discussed some basic NumPy techniques that can be used if you are starting out as a Python programmer. I mentioned matrix multiplication, transpose, how to calculate mean, median, standard deviation, etc. In this, I’ll be talking about more basic operations involved in NumPy like shape, reshape arrays in 3D, arrange function, zeros, etc. Reshaping is one of the most important techniques that is used in machine learning and deep learning. Let’s start There are a lot of other ways to create arrays using NumPy. One of the most important parts of machine learning is the reshaping of the matrix. We can create an identity matrix and we can create a zero and one matrix of any matrix dimension. Now let’s move on to a bit more complex algorithm using np.linspace(). Classification Algorithms Explained in 30 Minutes - datamahadev.com.
Share: A Quick Review Guide for Classification in Machine Learning, Along with Some of the Most Used Classification Algorithm, All Explained in Under 30 Minutes. In the Machine Learning terminology, the process of Classification can be defined as a supervised learning algorithm that aims at categorizing a set of data into different classes. In other words, if we think of a dataset as a set of data instances, and each data instance as a set of features, then Classification is the process of predicting the particular class that that individual data instance might belong to, based on its features. Unlike regression where the target variable (i.e., the predicted value) belongs to a continuous distribution, in case of classification, the target variable is discrete. It can only be one of the various target classes in a given problem. For example, let’s say you are working on a cat-dog-classifier model that predicts whether the animal in a given image is a cat or a dog.
So, let’s get started. AI Pilot: How Deep Reinforcement Learning Might Change Aviation & Warfare Forever - datamahadev.com. Biggest AI Innovation in the field of Reinforcement Learning Yet- A Fully-Autonomous Fighter Jet System Artificial Intelligence just made another big leap, this time in a rather peculiar manner by defeating an F-16 Fighter Jet pilot 5-0 in a dogfight. Yes, an AI pilot (an algorithm developed by the US-based company Heron Systems), with a just few months of training over computer simulations destroyed one of the US Air Force’s most seasoned pilots with years of experience on flying F-16 fighter jets, in a simulated fight that lasted for 5 rounds, with 5 perfect wins. This unique turn of events occurred during the AlphaDogFight Trials— a program organized by the Pentagon-backed Defense Advanced Research Projects Agency (DARPA) to see whether autonomous flying systems could defeat an actual human pilot in a computer-simulated dogfight.
And with the phenomenal success the DARPA achieved, this is just getting started. The answer is— Deep Reinforcement Learning. What is Reinforcement Learning?