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Learn to use maximum likelihood estimation in R with this step-by-step guide. Understand the theory behind MLE and how to implement it in R
We are excited to launch 2 new practice problems - identify the apparels and predicting if a joke is funny or not. In addition, we have also released 3 new free courses on time series, credit risk and predicting sales of a supermarket.
Take a look at the top machine learning and data science GitHub repositories and Reddit discussions that were designed and created in June, 2018.
Guide to building recommendation engines from scratch in Python. Learn to build a recommendation engine using matrix factorization.
Learn about ensemble learning techniques, including simple & advanced methods like bagging and boosting, along with key algorithms. Read Now!
Take a look at the top machine learning and data science GitHub repositories and Reddit discussions that happened/were created in May, 2018.
Complete machine learning and data science interview guide for data science and machine learning interviews. Learn how to prepare and behave in interviews.
Get started with machine learning projects to kick-start your career. Learn data science by applying it and showcase your skills on your CV.
Data science and machine learning tools for non-programmers who are unfamiliar with coding. These tools eliminate programming skills used in model building
Hierarchical temporal memory (HTM) method for unsupervised learning provides a tool which brings different strengths to the table compared to RNNs & CNNs
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