figure - new student records with model predictions for grant recommendations we can clearly see from figure - that our model has predicted grant recommendation labels for both the new students thomas clearly being diligenthaving straight average and decent scoresis most likely to get the grant recommendation as compared to nathan thus you can see that our model has learned how to predict grant recommendation outcomes based on past historical student data this should whet your appetite on getting started with machine learning we are about to deep dive into more complex real-world problems in the upcoming challenges in machine learning machine learning is rapidly evolvingfast-pacedand exciting field with lot of prospectopportunityand scope however it comes with its own set of challengesdue to the complex nature of machine learning methodsits dependency on dataand not being one of the more traditional computing paradigms the following points cover some of the main challenges in machine learning data quality issues lead to problemsespecially with regard to data processing and feature extraction data acquisitionextractionand retrieval is an extremely tedious and time consuming process lack of good quality and sufficient training data in many scenarios formulating business problems clearly with well-defined goals and objectives feature extraction and engineeringespecially hand-crafting featuresis one of the most difficult yet important tasks in machine learning deep learning seems to have gained some advantage in this area recently overfitting or underfitting models can lead to the model learning poor representations and relationships from the training data leading to detrimental performance the curse of dimensionalitytoo many features can be real hindrance complex models can be difficult to deploy in the real world this is not an exhaustive list of challenges faced in machine learning todaybut it is definitely list of the top problems data scientists or analysts usually face in machine learning projects and tasks we will cover dealing with these issues in detail when we discuss more about the various stages in the machine learning pipeline as well as solve real-world problems in subsequent real-world applications of machine learning machine learning is widely being applied and used in the real world today to solve complex problems that would otherwise have been impossible to solve based on traditional approaches and rule-based systems the following list depicts some of the real-world applications of machine learning