Fur­ther read­ing

Mac Format - - APPLE CORE -


If you’re in­ter­ested in learn­ing more about ma­chine learn­ing, or want to start cre­at­ing apps that make use of such tech­nol­ogy, take a look at the fol­low­ing re­sources.

Ap­ple ex­plain­ers

Ap­ple has pub­lished pages ex­plain­ing how its de­vices use ma­chine learn­ing, from Face ID (bitly.com/facei­dml) to Sa­fari’s In­tel­li­gent Track­ing Pre­ven­tion (bitly.com/sa­fariml).

Royal So­ci­ety

The Royal So­ci­ety (bitly.com/royscml) has a good in­tro­duc­tion to ma­chine learn­ing that com­bines in­ter­ac­tive in­fo­graph­ics with ac­ces­si­ble ex­pla­na­tions to de­mys­tify the topic.

Tech com­pany blogs

Ap­ple forewent its usual se­crecy when it launched its Ma­chine Learn­ing Jour­nal (bitly.com/apml­blog) in 2017. It goes into great depth on top­ics such as Hey Siri de­tec­tion and hand­writ­ing recog­ni­tion. Mi­crosoft (bitly.com/ msml­blog) and Google (bitly.com/ googleml­blog) pub­lish sim­i­lar pages.

De­vel­oper re­sources from Ap­ple

Ap­ple has a set of re­sources at bitly. com/ap­plml to help de­vel­op­ers cre­ate apps with Core ML 2 and Cre­ate ML, frame­works used to make ma­chine learn­ing-based apps in iOS and macOS.

IBM Sum­mit

IBM’s Sum­mit su­per­com­puter (bitly. com/ibmsmmt) is claimed to be the fastest in the world. It’s used to model su­per­novas, pi­o­neer new ma­te­ri­als and ex­plore can­cer, ge­net­ics and the en­vi­ron­ment us­ing ma­chine learn­ing.

Back to school

Sev­eral UK unis run post-grad cour­ses in ma­chine learn­ing, in­clud­ing Im­pe­rial Col­lege Lon­don (bitly.com/impml) and Manch­ester (bitly.com/mancml).

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