Destruction AllStars is a helluva lot better following its reboot earlier this week, and you can find out more about what’s improved in our hands on. The big battle for Lucid Games is now getting people to try it, and while many will have the title in their PlayStation 5 library following its PS Plus run last year, there’s a suggestion that it may go free-to-play.
Eagle-eyed Reddit users spotted during a period of server maintenance this week that the new-set of Welcome Challenges in the game – onboarding tasks which reward you with XP and in-game currency for completing some fairly simple starter tasks – were labelled in the source code as ‘F2P’, potentially signalling some kind of free-to-play re-release. It’d make sense, seeing as the title is clearly inspired by the likes of Fortnite and Apex Legends.
This article was published as a part of the Data Science Blogathon. Introduction Named Entity Recognition(NER) is a subtask of information extraction that locates and classifies different entities like name, organization, person, etc., in a sentence. Usually, it is done to classify named entities mentioned in unstructured text into predefined categories. Named Entity Recognition(NER) has many […]
This article was published as a part of the Data Science Blogathon. Introduction A Machine Learning solution to an unambiguously defined business problem is developed by a Data Scientist ot ML Engineer. The Model development process undergoes multiple iterations and finally, a model which has acceptable performance metrics on test data is taken to the production […]
This article was published as a part of the Data Science Blogathon. Source: medium.com Hey Folks! Welcome to the NLP article series. so far we have covered the multiple text processing techniques in the first article. In the second part of the NLP article series, we saw different types of feature extraction techniques and word […]
This article was published as a part of the Data Science Blogathon. Whether you’ve been in the Data Science and Machine Learning arena for quite some time or have just stepped into this exciting avenue – you sure have stumbled upon Python’s popular Machine Learning model building library, you guessed it right – Scikit learns. One […]
Introduction Text is all we need. Everything we speak, write carries a huge amount of information. The topic name of the article, tone of the article everything adds a piece of information that we can interpret and extract the insights from them. Processing text and extracting the important information from the text is text processing. Doing data analysis by extracting […]
This article was published as a part of the Data Science Blogathon. A centralized location for research and production teams to govern models and experiments by storing metadata throughout the ML model lifecycle. Introduction When working on a machine learning project, it’s one thing to receive impressive results from a single model-training run. Keeping track of […]
This article was published as a part of the Data Science Blogathon. Introduction Over the past several years, groundbreaking developments in machine learning and artificial intelligence have reshaped the world around us. There are various deep learning algorithms that bring Machine Learning to a new level, allowing robots to learn to discriminate tasks utilizing the human […]
This article was published as a part of the Data Science Blogathon. Table of Contents 1) Introduction 2) Types of Errors 3) Types of Hypothesis Tests 4) All about Parametric and Non-Parametric Tests 5) Parametric vs Non-Parametric Tests 6) Hypothesis Tests of the Mean and Median 7) Reasons to use Parametric Tests 8) Reasons to use […]
