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Data Science & Machine Learning Newsletter # 58

I share the arti­cles took my atten­tion and pub­lish ‘Data Sci­ence & Machine Learn­ing Newslet­ter’ every Fri­day. If you want to get updates, please join ‘Data Sci­ence & Machine Learn­ing Newslet­ter Linkedin Group’. Machine Learn­ing – Anom­aly Detec­tion: “Find­ing a Nee­dle in a Haystack”  After explor­ing for­mu­la­tion, clas­si­fi­ca­tion, bench­mark­ing, we explore another facet of Machine Learn­ing: anom­aly detec­tion. This part is key in the IoT trans­for­ma­tion, as it enables internet-connected Devamını Oku […]

Data Science & Machine Learning Newsletter # 57

I share the arti­cles took my atten­tion and pub­lish ‘Data Sci­ence & Machine Learn­ing Newslet­ter’ every Fri­day. If you want to get updates, please join ‘Data Sci­ence & Machine Learn­ing Newslet­ter Linkedin Group’. Data sci­ence with­out sta­tis­tics is pos­si­ble, even desir­able The pur­pose of this arti­cle is to clar­ify a few mis­con­cep­tions about data and sta­tis­ti­cal sci­ence. I will start with a con­tro­ver­sial state­ment: data sci­ence barely uses sta­tis­ti­cal sci­ence and tech­niques. The truth Devamını Oku […]

Data Science & Machine Learning Newsletter # 56

I share the arti­cles took my atten­tion and pub­lish ‘Data Sci­ence & Machine Learn­ing Newslet­ter’ every Fri­day. If you want to get updates, please join ‘Data Sci­ence & Machine Learn­ing Newslet­ter Linkedin Group’. Neural Net­works for Banks’ Pat­tern Recog­ni­tion Under the rea­son­able assump­tion that the finan­cial posi­tion of a firm is unique and rep­re­sen­ta­tive, we use a basic arti­fi­cial neural net­work pat­tern recog­ni­tion method on Colom­bian banks’ 2000–2014 monthly 25-account bal­ance Devamını Oku […]

Data Science & Machine Learning Newsletter # 55

I share the arti­cles took my atten­tion and pub­lish ‘Data Sci­ence & Machine Learn­ing Newslet­ter’ every Fri­day. If you want to get updates, please join ‘Data Sci­ence & Machine Learn­ing Newslet­ter Linkedin Group’. Machine learn­ing is at peak in Gart­ner Hype cycle                         Field Guide to Con­ti­nous Prob­a­bil­ity Dis­tri­b­u­tions Dig­i­tal­Globe, Cos­miQ Works, NVIDIA, and Ama­zon Devamını Oku […]

Data Science & Machine Learning Newsletter # 54

I share the arti­cles took my atten­tion and pub­lish ‘Data Sci­ence & Machine Learn­ing Newslet­ter’ every Fri­day. If you want to get updates, please join ‘Data Sci­ence & Machine Learn­ing Newslet­ter Linkedin Group’. How Con­vo­lu­tional Neural Net­works Work Nine times out of ten, when you hear about deep learn­ing break­ing a new tech­no­log­i­cal bar­rier, Con­vo­lu­tional Neural Net­works are involved. Also called CNNs or Con­vNets, these are the work­horse of the deep neural net­work field. Rein­force­ment Devamını Oku […]

Data Science & Machine Learning Newsletter # 53

I share the arti­cles took my atten­tion and pub­lish ‘Data Sci­ence & Machine Learn­ing Newslet­ter’ every Fri­day. If you want to get updates, please join ‘Data Sci­ence & Machine Learn­ing Newslet­ter Linkedin Group’. How Expedia.com was built on machine learn­ing Machine learn­ing is at the peak of the hype scale, but travel search giant Expe­dia has been build­ing its core busi­ness on the tech­nol­ogy for the best part of a decade. node2vec: Scal­able Fea­ture Learn­ing for Net­works node2vec Devamını Oku […]

Data Science & Machine Learning Newsletter # 52

I share the arti­cles took my atten­tion and pub­lish ‘Data Sci­ence & Machine Learn­ing Newslet­ter’ every Fri­day. If you want to get updates, please join ‘Data Sci­ence & Machine Learn­ing Newslet­ter Linkedin Group’. Deep Learn­ing, NLP, and Rep­re­sen­ta­tions This post reviews some extremely remark­able results in apply­ing deep neural net­works to nat­ural lan­guage pro­cess­ing (NLP). In doing so, I hope to make acces­si­ble one promis­ing answer as to why deep neural net­works work. Automat­ing Devamını Oku […]

Data Science & Machine Learning Newsletter # 51

I share the arti­cles took my atten­tion and pub­lish ‘Data Sci­ence & Machine Learn­ing Newslet­ter’ every Fri­day. If you want to get updates, please join ‘Data Sci­ence & Machine Learn­ing Newslet­ter Linkedin Group’. Researchers use neural net­works to turn face sketches into pho­tos A team of four neu­ro­sci­en­tists at Rad­boud Uni­ver­sity is work­ing on a model for invert­ing face sketches to syn­the­size pho­to­re­al­is­tic face images by using deep neural net­works. 7 Types of Regres­sion Tech­niques Devamını Oku […]

Data Science & Machine Learning Newsletter # 50

I share the arti­cles took my atten­tion and pub­lish ‘Data Sci­ence & Machine Learn­ing Newslet­ter’ every Fri­day. If you want to get updates, please join ‘Data Sci­ence & Machine Learn­ing Newslet­ter Linkedin Group’. Gra­di­ent Boost­ing Inter­ac­tive Play­ground Inter­ac­tive demonstration-explanation of gra­di­ent boost­ing algo­rithm applied to clas­si­fi­ca­tion prob­lem Edward: A library for prob­a­bilis­tic mod­el­ing, infer­ence, and crit­i­cism A Python library for prob­a­bilis­tic mod­el­ing, infer­ence, Devamını Oku […]

Data Science & Machine Learning Newsletter # 49

I share the arti­cles took my atten­tion and pub­lish ‘Data Sci­ence & Machine Learn­ing Newslet­ter’ every Fri­day. If you want to get updates, please join ‘Data Sci­ence & Machine Learn­ing Newslet­ter Linkedin Group’. MNIST Gen­er­a­tive Adver­sar­ial Model in Keras Some of the gen­er­a­tive work done in the past year or two using gen­er­a­tive adver­sar­ial net­works (GANs) has been pretty excit­ing and demon­strated some very impres­sive results.  The gen­eral idea is that you train two mod­els, one (G) Devamını Oku […]