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Fermat's last conjecture has puzzled mathematicians for 300 years, and was eventually proved only recently. In this note, I propose a generalization, that could actually lead to a much simpler proof and a more powerful result with broader applications, including to solve numerous similar equations. As usual, my research involves a significant amount of computations and experimental math, as an exploratory step before stating new conjectures, and eventually trying to prove them. The…
ContinueAdded by Vincent Granville on January 30, 2020 at 1:09am — No Comments
Hundreds of programming languages dominate the data science and statistics market: Python, R, SAS and SQL are standouts. If you're looking to branch out and add a new programming language to your skill set, which one should you learn? This one picture breaks down the differences between the four languages.…
ContinueAdded by Vincent Granville on January 28, 2020 at 8:41pm — No Comments
While many of the programming libraries encapsulate the inner working details of graph and other algorithms, as a data scientist it helps a lot having a reasonably good familiarity of such details. A solid understanding of the intuition behind such algorithms not only helps in appreciating the logic behind them but also helps in making conscious decisions about their applicability in real life cases. There are several graph based algorithms and most notable are the shortest path…
ContinueAdded by Vincent Granville on January 21, 2020 at 10:12am — No Comments
In 2019, Google announced TensorFlow 2.0, it is a major leap from the existing TensorFlow 1.0. The key differences are as follows:
Ease of use: Many old libraries (example tf.contrib) were removed, and some consolidated. For example, in TensorFlow1.x the model could be made using Contrib, layers, Keras or estimators, so many options for the same task confused many new users. TensorFlow 2.0 promotes TensorFlow Keras for model experimentation and Estimators…
ContinueAdded by Vincent Granville on January 9, 2020 at 9:49am — No Comments
Summary: AI/ML itself is the next big thing for many fields if you’re on the outside looking in. But if you’re a data scientist it’s possible to see those advancements that will propel AI/ML to its next phase of utility.
“The Next Big Thing in AI/ML is…” as the lead to an article is probably the most…
Added by Vincent Granville on January 7, 2020 at 7:41am — No Comments
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