其實想問問,有無巴打識寫text mining d programs? 成日都淨係識用現成,唔識改
自己寫python scripts 抽txt 入面既data
但都係抽我d experiment data
所以有pattern係度
其他要摸索下
完全唔識python coding
我學過python, 但係一d好簡單既syntax
其實想問問,有無巴打識寫text mining d programs? 成日都淨係識用現成,唔識改
自己寫python scripts 抽txt 入面既data
但都係抽我d experiment data
所以有pattern係度
其他要摸索下
完全唔識python coding
揾左Researh associate
諗住做一排先上phD
揾左Researh associate
諗住做一排先上phD
Associate多數係PhD既位,巴打咁勁
揾左Researh associate
諗住做一排先上phD
Associate多數係PhD既位,巴打咁勁
揾左Researh associate
諗住做一排先上phD
Associate多數係PhD既位,巴打咁勁
唔係喎! 我係poly research associate
Master 就得
揾左Researh associate
諗住做一排先上phD
Associate多數係PhD既位,巴打咁勁
唔係喎! 我係poly research associate
Master 就得
揾左Researh associate
諗住做一排先上phD
Associate多數係PhD既位,巴打咁勁
唔係喎! 我係poly research associate
Master 就得
想八下幾時人工到
有巴打係搞Machine Learning?我係報緊ML PhD (但係係報PhD in Stat)
computer vision算唔算
睇你做咩computer vision
黎緊mphil做果樣算係pattern recognition/classification
應該用CNN做
巴打係bayes果邊?我聽就聽得多 成套machine learning真係講唔上熟練
如果入到Oxford就肯定係做Bayesian 慢慢學 但MPhil兩年真係學唔到好多
識個phd 佢mphil都係做bayes果邊 而家就玩緊random forest/metric果d
我始終係stat佬 statistical machine learning research宜家多數Bayesian
唔似CS果邊咁algorithmically driven
揾左Researh associate
諗住做一排先上phD
Associate多數係PhD既位,巴打咁勁
有巴打係搞Machine Learning?我係報緊ML PhD (但係係報PhD in Stat)
computer vision算唔算
睇你做咩computer vision
黎緊mphil做果樣算係pattern recognition/classification
應該用CNN做
巴打係bayes果邊?我聽就聽得多 成套machine learning真係講唔上熟練
如果入到Oxford就肯定係做Bayesian 慢慢學 但MPhil兩年真係學唔到好多
識個phd 佢mphil都係做bayes果邊 而家就玩緊random forest/metric果d
我始終係stat佬 statistical machine learning research宜家多數Bayesian
唔似CS果邊咁algorithmically driven
咁而家果套背後都係optimization/randomness driven既
我自己stat唔係幾好 ug skip左multivariate,
但係偏偏遲下pub文係用類似random projection做dimension reduction
有d方向就係manifold既classification(LDA), 唔sure仲heat唔heat
睇你做咩computer vision
黎緊mphil做果樣算係pattern recognition/classification
應該用CNN做
巴打係bayes果邊?我聽就聽得多 成套machine learning真係講唔上熟練
如果入到Oxford就肯定係做Bayesian 慢慢學 但MPhil兩年真係學唔到好多
識個phd 佢mphil都係做bayes果邊 而家就玩緊random forest/metric果d
我始終係stat佬 statistical machine learning research宜家多數Bayesian
唔似CS果邊咁algorithmically driven
咁而家果套背後都係optimization/randomness driven既
我自己stat唔係幾好 ug skip左multivariate,
但係偏偏遲下pub文係用類似random projection做dimension reduction
有d方向就係manifold既classification(LDA), 唔sure仲heat唔heat
用家表示:dimension reduction嘅方法仲有發展空間
有巴打係搞Machine Learning?我係報緊ML PhD (但係係報PhD in Stat)
computer vision算唔算
睇你做咩computer vision
黎緊mphil做果樣算係pattern recognition/classification
應該用CNN做
巴打係bayes果邊?我聽就聽得多 成套machine learning真係講唔上熟練
如果入到Oxford就肯定係做Bayesian 慢慢學 但MPhil兩年真係學唔到好多
識個phd 佢mphil都係做bayes果邊 而家就玩緊random forest/metric果d
我始終係stat佬 statistical machine learning research宜家多數Bayesian
唔似CS果邊咁algorithmically driven
咁而家果套背後都係optimization/randomness driven既
我自己stat唔係幾好 ug skip左multivariate,
但係偏偏遲下pub文係用類似random projection做dimension reduction
有d方向就係manifold既classification(LDA), 唔sure仲heat唔heat
睇你做咩computer vision
黎緊mphil做果樣算係pattern recognition/classification
應該用CNN做
巴打係bayes果邊?我聽就聽得多 成套machine learning真係講唔上熟練
如果入到Oxford就肯定係做Bayesian 慢慢學 但MPhil兩年真係學唔到好多
識個phd 佢mphil都係做bayes果邊 而家就玩緊random forest/metric果d
我始終係stat佬 statistical machine learning research宜家多數Bayesian
唔似CS果邊咁algorithmically driven
咁而家果套背後都係optimization/randomness driven既
我自己stat唔係幾好 ug skip左multivariate,
但係偏偏遲下pub文係用類似random projection做dimension reduction
有d方向就係manifold既classification(LDA), 唔sure仲heat唔heat
用家表示:dimension reduction嘅方法仲有發展空間
睇你做咩computer vision
黎緊mphil做果樣算係pattern recognition/classification
應該用CNN做
巴打係bayes果邊?我聽就聽得多 成套machine learning真係講唔上熟練
如果入到Oxford就肯定係做Bayesian 慢慢學 但MPhil兩年真係學唔到好多
識個phd 佢mphil都係做bayes果邊 而家就玩緊random forest/metric果d
我始終係stat佬 statistical machine learning research宜家多數Bayesian
唔似CS果邊咁algorithmically driven
咁而家果套背後都係optimization/randomness driven既
我自己stat唔係幾好 ug skip左multivariate,
但係偏偏遲下pub文係用類似random projection做dimension reduction
有d方向就係manifold既classification(LDA), 唔sure仲heat唔heat
manifold係咩
睇你做咩computer vision
黎緊mphil做果樣算係pattern recognition/classification
應該用CNN做
巴打係bayes果邊?我聽就聽得多 成套machine learning真係講唔上熟練
如果入到Oxford就肯定係做Bayesian 慢慢學 但MPhil兩年真係學唔到好多
識個phd 佢mphil都係做bayes果邊 而家就玩緊random forest/metric果d
我始終係stat佬 statistical machine learning research宜家多數Bayesian
唔似CS果邊咁algorithmically driven
咁而家果套背後都係optimization/randomness driven既
我自己stat唔係幾好 ug skip左multivariate,
但係偏偏遲下pub文係用類似random projection做dimension reduction
有d方向就係manifold既classification(LDA), 唔sure仲heat唔heat
manifold係咩
巴打會唔會唔識呀
我都係睇d人講先驚醒可以有關
如果入到Oxford就肯定係做Bayesian 慢慢學 但MPhil兩年真係學唔到好多
識個phd 佢mphil都係做bayes果邊 而家就玩緊random forest/metric果d
我始終係stat佬 statistical machine learning research宜家多數Bayesian
唔似CS果邊咁algorithmically driven
咁而家果套背後都係optimization/randomness driven既
我自己stat唔係幾好 ug skip左multivariate,
但係偏偏遲下pub文係用類似random projection做dimension reduction
有d方向就係manifold既classification(LDA), 唔sure仲heat唔heat
manifold係咩
巴打會唔會唔識呀
我都係睇d人講先驚醒可以有關
中過伏, 聽過Applied Math的talk講manifold, 但係原來同我認識的manifold係兩樣野黎, 所以問清楚
睇你做咩computer vision
黎緊mphil做果樣算係pattern recognition/classification
應該用CNN做
巴打係bayes果邊?我聽就聽得多 成套machine learning真係講唔上熟練
如果入到Oxford就肯定係做Bayesian 慢慢學 但MPhil兩年真係學唔到好多
識個phd 佢mphil都係做bayes果邊 而家就玩緊random forest/metric果d
我始終係stat佬 statistical machine learning research宜家多數Bayesian
唔似CS果邊咁algorithmically driven
咁而家果套背後都係optimization/randomness driven既
我自己stat唔係幾好 ug skip左multivariate,
但係偏偏遲下pub文係用類似random projection做dimension reduction
有d方向就係manifold既classification(LDA), 唔sure仲heat唔heat
用家表示:dimension reduction嘅方法仲有發展空間
令我諗起 curse of dimensionality
Maryland都有offer
估唔到
其實想問問,有無巴打識寫text mining d programs? 成日都淨係識用現成,唔識改
自己寫python scripts 抽txt 入面既data
但都係抽我d experiment data
所以有pattern係度
其他要摸索下
完全唔識python coding
我學過python, 但係一d好簡單既syntax
Maryland都有offer
估唔到
其實想問問,有無巴打識寫text mining d programs? 成日都淨係識用現成,唔識改
自己寫python scripts 抽txt 入面既data
但都係抽我d experiment data
所以有pattern係度
其他要摸索下
完全唔識python coding
我學過python, 但係一d好簡單既syntax
其實有無得自學 唔知點入手
其實想問問,有無巴打識寫text mining d programs? 成日都淨係識用現成,唔識改
自己寫python scripts 抽txt 入面既data
但都係抽我d experiment data
所以有pattern係度
其他要摸索下
完全唔識python coding
我學過python, 但係一d好簡單既syntax
其實有無得自學 唔知點入手
我個時係上coursera學,我諗而家應該重有!