Python罘罌医膺違潟 PyTorch鐚scikit-learn膩

Python罘罌医膺違潟 PyTorch鐚scikit-learn膩

4,620鐚篏 4,200鐚腮10%鐚

腮
悟
阪２
2022/12/15
若御
712
泣ゃ
B5紊綵√
Sebastian Raschka/Yuxi (Hayden) Liu/Vahid Mirjalili/綣鋍腓障ゃ若荐/胼鎤句紊ｄ信
ISBN
9784295015581

茫PyTorch羈障с種

膃3障х潟違祉若PyTorch鐚 罘罌医膺堺PyTorch牙羈障ф取В茯吾絎罘罌医膺ゃscikit-learn羈茹ｈ堺≪絮ゃャ若障у茖祉若水罨≦羝ゃ若＜若帥若≪潟泣潟絖膺絽医筝障緇PyTorch篁腟帥茯CNN鐚RNN鐚Transformer絎茖茹ｈGAN違ャ若若綣桁絖膺若堺茫PyTorch絎莊泣障у絖鴻筝с

罨＜荀

4,620
鐚篏 4,200鐚腮10%鐚

PDF / 医隙 / 90MB / 純若激ｃDRM

頑鴬糸ゃ

ゃ潟鴻ч糸莢激鐚若ャ障鐚

茯≪潟宴若膈茯若潟綽翫＜

≪潟宴若膈

悟絎鴻≪＜膈с吾荐莠絎鴻≪障

若

荅潟荐罩

絖＜紙篋坂莖弱ャ≪＜吾

筝莖弱ョ

荅括完

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膣剛


Dr. Sebastian Raschka
ｃ鴻潟潟激喝腴紊уｃ純恰＜腟沿絖罘罌医膺羞怨韻絖膺腥吟羈
若潟純若鴻怨莢∝сGrid.aiAI蚊若篋阪轡ヨ純潟や査叵違綵劫蚊篋絎

Yuxi (Hayden) Liu
違若違罘罌医膺純с≪潟吾≪筝紊с罎膣≪潟吾潟綺罘罌医膺≪鐚激鴻冴紙壕腟с
障с障障若翠＜ゃ潟罐罘罌医膺泣ゃ潟ｃ鴻緇篋

Dr. Vahid Mirjalili
潟潟ャ若帥吾с潟≪宴若激с潟劫ｃ若若潟違腥区
激喝腴紊у罘罌医轡絖潟潟ャ若帥泣ゃ潟鴻筝≧鴻у紕垩緇
紕茯牙с絎筝馹茹ｆ浦潟潟ャ若帥吾с潟違≪眼冴冴綣紊腥区ゃ肴；

膺肢┳
綣鋍腓障ゃ若
1995綛眼膠喝純泣潟潟激鴻潟荐腴潟潟ャ若帥激鴻冴若ゃ冴潟潟泣ｃ潟違2001綛眼ユ羈篋冴荐腴筝祉荐恰吾違若ャｃ40≪眼冴 絎紙亥鎧Pythonу莊居鐚紫3鐚Python罘罌医膺違潟 篋冴若帥泣ゃ潟ｃ鴻茫絎莊泣Amazon Web Servicesゃ潟泣若号柑紊у 激鴻罕膀/若帥鴻≪蕭篆♂弱鐚ゃ潟合肴鐚www.quipu.co.jp

ｈ┳
胼鎤 紊
憜篌罐ф罌医膺若帥ゃ潟違腥狗冴茵冴罐緇篋
延根紊у絖絖腱罐延根紊у紊у∽育究腱絖腥句 茲綏ュ絨 篆紕茯牙篆篋延根紊у紊у∽援綏ュ膤紫腥句 亥怨絨 紕茯牙篆篋紕鐚援綏ュ鐚絨祉罘罌医膺祉若帥ゃ潟違脂膩綵√絖膤祉

罨

膃1腴 若帥絖膺遵潟潟ャ若帥筝
膃2腴 蕁馹膣罘罌医膺≪眼冴荐膩
膃3腴 蕁馹罘罌医膺ゃscikit-learn羇紫
膃4腴 若水荐膩眼若帥祉罕膀
膃5腴 罨≦羝с若帥х軒
膃6腴 ≪荅箴＜ゃ若＜若帥ャ若潟違鴻ｃ
膃7腴 ≪潟泣潟絖膺違≪腟水
膃8腴 罘罌医膺
膃9腴 絽医ｇゃ紊違篋羝
膃10腴 鴻水若帥
膃11腴 紊絮や査綏ャャ若若筝絎茖
膃12腴 ャ若若荐膩眼PyTorchт研
膃13腴 PyTorch＜冴
膃14腴 糸蕁ｃ若潟粋昭帥ャ若若
膃15腴 膤糸若帥≪潟ャ若若
膃16腴 TransformerAttention＜冴区茯劫
膃17腴 違若帥球丞若
膃18腴 違ャ若若違罕若帥с箴絖с
膃19腴 茲医с羆阪綣桁絖膺

∫ｆ悟

菴ョ阪２

PythonMCPу茖AI若吾с潟榊ゃ潟榊潟若荐荐鐚顄荐取鐚障

PythonMCPу茖AI若吾с潟榊ゃ潟榊潟若荐荐鐚顄荐取鐚障

蕭綺AIｆ冴祉ャｅ茖種

菴ョ阪２

絎茹ｈ鐚Claude Code

絎茹ｈ鐚Claude Code

菴ョ阪２

吟уLLM絎茖ラGoogle Colaboratoryу莊泣LLMRAG祉＜ゃ潟ャ若潟

吟уLLM絎茖ラGoogle Colaboratoryу莊泣LLMRAG祉＜ゃ潟ャ若潟

筝荳ｃLLM帥鐚

絅処阪２筝

≪Transformer≪罕≪若鐚RAG鐚SLM絎茖障

≪Transformer≪罕≪若鐚RAG鐚SLM絎茖障

罕潟若茹ｃ腆冴絎茖鐚

潟若

茖遵茯障絲乗院潟若宴障

荅潟荐罩

茯よ菴傑茯潟荐潟障

  • 0若 ｇ亀v若吾若娯糸鐚P.92糸鐚
    • [茯]
      私荐荐罩ｃ障
    • [罩]
    • 膃2激篆罩
  • 38若 膓我帥鏅綣4茵緇
    • [茯]
      私札筝荐罩ｃ障
    • [罩]
    • 膃2激篆罩
  • 38若 膓我ゃ≪鴻鏅綣1茵
    • [茯]
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    • [罩]
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  • 62若 綣3.3.9勈昇
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      私札筝荐罩ｃ障
    • [罩]
    • 膃2激篆罩
  • 66若 潟若筝15-16茵
    • [茯]
      loss = (-y.dot(np.log(output)) -
      ((1 - y).dot(np.log(1 - output))) / X.shape[0]
    • [罩]
      loss = (-y.dot(np.log(output)) -
      (1 - y).dot(np.log(1 - output))) / X.shape[0]
    • 膃2激篆罩
  • 66若 潟若潟＜潟3茵
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    • 膃2激篆罩
  • 91若 若娯臀潟若2茵
    • [茯]
      feature_names = ['Sepal length', 'Sepal width', 'Petal length', 'Petal width']
    • [罩]
      feature_names = ['Petal length', 'Petal width']
    • 膃2激篆罩
  • 92若 3-23
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      私荐紊器ｇ亀v若吾罕紊器
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      8.11.
    • [罩]
      1.4.紊
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  • 139若 5.1.4膊≧吾医
    • [茯]
      12.14.
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      5.7.紊
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  • 148若 5.2.2膊≧吾医
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  • 149若 綣(5.2.2)
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  • 180若 6.4.3膊≧吾医
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      5.8.
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  • 183若 6.5膀帥ゃ翫
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      ャ絖篋ゅ勲罎荐若с≪御祉
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  • 193若 臀蚊帥潟若筝
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      ≪泣潟潟違0泣祉腟с
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  • 216若 1茵
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  • 274若 綣9.5.2翫罧笈純1茵
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    • 膃2激篆罩
  • 274若 綣9.5.2翫罧笈純4鐔6茵罧笈純緇
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      MSE綛恰号鴻сRMSE鐚root mean squared error鐚荐膊帥RMSE綛喝腟九乗ゅ勲鐚mean absolute error鐚MAE鐚若違с罩ｃ篋羝若篁ュ祉綣決帥
    • [罩]
      MSE綛恰号鴻сRMSE鐚root mean squared error鐚荐膊障罩ｃ篋羝ゃ篁ュ祉綣決帥綛喝腟九乗ゅ勲鐚mean absolute error鐚MAE鐚荐膊с
    • 膃2激篆罩
  • 295若 若御絨障腟茵
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  • 320若 綣(11.1.8)綣絨障ゃ≪鴻菴遵
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      私札筝荐罩ｃ障鐚4激2025/4/16堺ワ
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    • 膃4激篆罩
  • 332若 1ょ臀潟若筝3茵
    • [茯]
      mse = mse/i
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      mse = mse/(i+1)
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  • 338若 綣11.3.1翫筝
    • [茯]
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  • 339若 11-10茯
    • [茯]
      W^{(h)}鐚鐚茵鐚劫彰鐚鐚
      W^{(out)}鐚阪鐚茵鐚鐚鐚
    • [罩]
      W^{(h)}鐚劫彰鐚茵鐚鐚鐚
      W^{(out)}鐚鐚茵鐚阪鐚鐚
    • 膃5激篆罩
  • 342若 綣11.3.8勈昇y筝篁羞祉絖1綽荀
    • [茯]
      = 2(a1^(out)-y)
    • [罩]
      = 2(a1^(out)-y_1)
    • 膃5激篆罩
  • 355若 臀潟若筝2茵
    • [茯]
      潟純泣ゃ冴chunksゃу蚊翫緇ｃ潟絨
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      潟純泣ゃ冴ｃ潟ゃу蚊翫с緇ｃ潟違絽吾絎ゃ筝鐚絽吾緇鐚ｃ潟泣ゃ冴篁絨
    • 膃5激篆罩
  • 413若 潟若潟＜潟
    • [茯]
      # Lightning 違絮
    • [罩]
      # Lightning 違絮
      # Torchmetrics 0.8.0 篁ラс罨＜紊眼綽荀鐚
      # self.train_acc = Accuracy(task="multiclass", num_classes=10)
    • 膃2激篆罩
  • 433若 臀潟若12茵篁ラfor若
  • 483若 若娯賢紊絨筝臀潟若6茵ゃ
    • [茯]
      祉若娯筝荐羈菴遵
    • [罩]
      鐚肢┳羈鐚torch 1.9.0鐚torchtext 0.10.0腟水篁ュсtest_dl = DataLoader(list(test_dataset), batch_size=batch_size, ... 紊眼綽荀
    • 膃2激篆罩
  • 553若 若娯羈82
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  • 554若 綣鐚17.1.5鐚
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悟絎鴻≪＜膈с吾荐莠絎鴻≪障

若