Kaggle is used by almost every data science aspirant. It contains datasets for all domains. You can get a dataset for just about every use case, including entertainment, medicine, e-commerce, and even astronomy. Its users can practise on a variety of datasets to see how well they know Data Science…

Frameworks such as Tensorflow, Pytorch, Theano and Cognitive Toolkit (CNTK) (and by extension any deep learning library which works alongside them, e.g. Keras) permit significantly faster training of deep learning when they are set up with GPU (graphics processing unit) support compared withusing a CPU. …

Q1. Show the working of the Minimax algorithm using Tic-Tac-Toe Game. There are two players involved in a game: MAX: This player tries to get the highest possible score MIN: MIN tries to get the lowest possible score The following approach is taken for a Tic-Tac-Toe game using the Minimax algorithm: Step 1: First, generate the entire game tree starting with…

Q1. How does Reinforcement Learning work? Explain with an example. Generally, a Reinforcement Learning (RL) system is comprised of two main components: An agent An environment The environment is the setting that the agent is acting on and the agent represents the RL algorithm. The RL process starts when the environment sends a state to the agent, which then based…

Q1. What is the difference between AI, Machine Learning and Deep Learning? Artificial IntelligenceMachine LearningDeep Learning Originated in 1950s Originated in 1960s Originated in 1970s AI represents simulated intelligence in machine ML is the practice of getting machines to make decisions without being programmed DL is the process of using Artificial Neural Networks to solve complex problems AI is a subset of…

The focus of supervised learning revolves around the input and output variables using an algorithm to predict the outcome. If a new input variable comes into the picture. The linear regression algorithm in machine learning is a supervised learning technique to approximate the mapping function to get the best predictions…

Overview of Machine Learning So for all those of you who do not know what is Machine Learning? Machine Learning, in the simplest of terms, is teaching your machine about something. You collect data, clean the data, create algorithms, teach the algorithm essential patterns from the data and then expect the algorithm to give…

Building a Machine Learning model is not just about feeding the data, there is a lot of deficiencies that affect the accuracy of any model. Overfitting in Machine Learning is one such deficiency in Machine Learning that hinders the accuracy as well as the performance of the model. …

What Is Machine Learning? In the year 1959, Arthur Samuel created the term “machine learning.” In terms of technological developments, that year was arguably the most significant. If you look up “what is Machine Learning” on the internet, you’ll get at least 100 distinct definitions. Tom M. …