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机器学习课程目录
8 z0 P# Z' r" U7 R4 E2 Q第01课.机器学习解决问题综述课.mp4
6 |: {" F3 Q$ {0 P: w% x第03课_kaggle案例实战班.mp4$ N; I% k$ K! o; u8 a
第04课_kaggle案例实战班.mp4
2 t' g" r! @5 L; y! O' h第05课_kaggle案例实战班.mp4
4 a7 O6 Q, I/ U; E! W( x! D第06课_kaggle案例实战班.mp4# {5 I6 M r" p
第07课_kaggle案例实战班.mp4
5 l% w6 u( c' j' s第08课_kaggle案例实战班.mp4$ {" r+ \, m. g# {+ @
第二节.mp4# C( ]0 R6 L9 x& t$ b Z$ v4 v
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0 W) q2 A( [+ ]( ^blending.py
N0 Z! V" s1 o& @* |cs228-python-tutorial.ipynb
" U5 x2 \8 }) V, k6 OFeature_engineering_and_model_tuning.zip6 m# p u- @) m) U4 c
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: F) ~+ S$ ^7 T& S: }Feature Engineering.ipynb
, {" |- a& w1 p- Z/ PTest.csv
9 \; y3 ?- @4 N2 ttest_modified.csv5 F7 j( H& g: ~' @+ [2 Z! }1 P
Train.csv
1 Q# f% g( e- X( J& Strain_modified.csv
) t3 l) t' `' f2 y- J8 [6 s, L) _XGBoost models tuning.ipynb
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Feature Engineering-checkpoint.ipynb
8 Z( x% m, H' @6 n @% U; H$ VXGBoost models tuning-checkpoint.ipynb3 v2 O& A- |; U$ p* Y' }3 \8 y
7 g# n+ k F: f- @: ^test.csv, e: }* H, J I( F
Titanic.ipynb
$ N, C' D3 ^( [- u5 G) F8 Itrain.csv
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Titanic-checkpoint.ipynb. C8 @9 b; |" t0 a
3 K1 v7 }! D5 D m1 A( a+ J+ PKaggle_Bicycle_Example.ipynb p5 g6 N. I( A! g: e
kaggle_bike_competition_train.csv
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Kaggle_Bicycle_Example-checkpoint.ipynb
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) w; N, b& G) h9 m2 u2 jKaggle_Bicycle_Example_34_0.png
8 q: u+ q! q; h4 [- a" I. i! oKaggle_Bicycle_Example_42_0.png
& c$ D \: h- T2 A8 q' u" A5 XKaggle_Bicycle_Example_43_0.png4 r3 \" G' w* r2 ?( q6 K
Kaggle_Bicycle_Example_44_0.png' V/ |# V8 @4 D) o. B1 x5 F2 n# m
Kaggle_Bicycle_Example_45_0.png
0 a/ U R9 d, X7 D+ b) m4 g( TKaggle_Bicycle_Example_46_1.png
9 l& d+ v5 C, D, ] g" N& ^8 i T$ DKaggle_Bicycle_Example_47_1.png
, a4 N. I9 c! qKaggle_Bicycle_Example_49_1.png
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, a. a( [. _. G& cdata_description.txt4 @/ v) T( l! ?
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: Q3 g, r3 l0 k. qsample_submission.csv' G1 R1 F% L8 y, j# A
test.csv
$ j }" x) j+ gtrain.csv
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house_price.html
& }7 i! b: M5 D) a5 y" ]house_price.ipynb: d! K! K6 a* B9 r( e3 {$ ]
house_price_advanced.html- r# u( t/ o; M# {
house_price_advanced.ipynb
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house_price_advanced-checkpoint.ipynb
2 r# T O( W+ k4 S2 Phouse_price-checkpoint.ipynb' F, K" y3 Z x1 L$ ]* X6 b [
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! e+ f: B/ u* R! E+ ~/ K0 Y3 _& q3 b9 ZCombined_News_DJIA.csv( V8 G1 d1 P x$ s* P
DJIA_table.csv
. j$ {) g; R- s% L: KRedditNews.csv/ m6 ^4 G( n4 O+ V/ p
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news_stock.html8 k6 y: H8 W. u: w w
news_stock.ipynb! a% ]: Q+ g* t% W" x
$ i V3 r# I* H* @' S3 Enews_stock-checkpoint.ipynb4 ?8 h, G6 [& V" I! L3 u2 s
" t$ b& {( n( N& D- p# e( Aavazu-CTR-Prediction-LR.zip% @. T# }8 I" h- U* P' U u3 h
feature.search
, }3 `# l# n1 L- h! c4 w" Lfeature.search_ads% V& p% X2 L3 P" ?; T0 E. Y
feature_map.search_ads
" B6 l) }, q/ x" n" L @# Rgenerate_train_feature_mapper.py% A' D5 j7 @5 u+ o' f" J* l
generate_train_feature_reducer.py
3 E) x9 j; `' j1 j/ ?8 r5 qkaggle-avazu-rank1.zip0 W+ p, ]; I9 e
kaggle-avazu-rank2.zip' A* \7 c/ d' U' x6 D% m& d
search_ads_feature.sample0 b U) Y% Z) z% W7 t3 q u: e
search_click_data.sample, X+ }5 C$ ~: A" @! Z$ [
Spark-Criteo-CTR-Prediction.ipynb
- p8 Z2 \2 `+ nxgb_ads.conf
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news_stock.html' ~; M# Z1 v, h. i
news_stock_advanced.html% y' L* V/ k/ T n
search relevance.ipynb" I' g" J8 v1 J
search relevance_advanced.ipynb
2 [. @) i# W8 v9 E/ v qsearch+relevance.html9 ?' O- y9 r0 h: O, K
search+relevance_advanced.html
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search relevance_advanced-checkpoint.ipynb3 A9 V: J5 E* z! r3 {! D
search relevance-checkpoint.ipynb
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1 f' A" r+ j, F9 Y* O9 jenergy_forecasting_notebooks.zip! ~% h0 ^. S1 y- B2 I
subway_prediction_notebook.zip
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% \3 u0 q) I! h1 `# [cat_dog.html" I9 [* o; F. m
char_rnn.html
! {; |& M/ K9 v% Dimage_search.html
2 y( \5 o1 ~4 j0 w6 ?) s f: BKaggle第06课：走起~深度学习.pdf
( L& z2 K4 ]. X$ UKaggle第06课：走起~深度学习.pptx/ M, t4 t% J2 E( a5 a
news_stock_advanced.html
' G; J9 ~/ d7 a& tword_rnn.html
# h7 m) b4 I$ e0 \& c<img>
* y$ j! w- @8 m; n2 Echi_square.png2 {/ L* i1 t) t, G- o
RGBHistogram.jpg
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cats-vs-dogs.txt5 h; D. i- N. m) r8 r$ [
sample_submission.csv
% ^1 `" h! ~" j$ W m' otest.zip: ?8 C) e; r- Y# x/ |2 y' q
train.zip
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data.zip. g5 `! i0 o0 f/ x/ Z
Kaggle event recommendation competition.ipynb
4 b+ ~8 R0 h$ {, Kkaggle-event-recommendation-rank1.zip
/ `1 V$ Z& C0 k' u# _Rossmann_Store_Sales_competition.ipynb" Q: ^& Y2 p" \3 w( X+ e
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PPD_RiskControl_Competition.zip
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Kaggle第05课：能源预测与分配问题.pdf
: ?6 D" i% G2 L! [Kaggle第06课：走起~深度学习.pdf
6 d# y' }. P2 q6 |& [) C4 LKaggle第06课：走起~深度学习.pptx! h2 K% s8 b; T/ ]% h4 t ^
$ r, g4 {$ Z/ p- l' w1 OKaggle第01课：机器学习算法、工具与流程概述.pdf0 ~6 t9 s. f! h0 w& k
分享的链接.txt
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Kaggle第02课：经济金融相关问题.pdf
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kaggle-2014-criteo.pdf
9 L4 Q6 ^; }" a6 Nkaggle-avazu.pdf3 l# c+ x7 [; L
predicting-clicks-facebook.pdf
4 ]) x8 L7 @9 p- Q. I阿里妈妈：大数据下的广告排序技术及实践.pdf
2 N9 @3 P Q7 x百度凤巢：DNN在凤巢CTR预估中的应用.pdf
) C; @4 \; ^4 D7 }5 h( j: e% S# }0 @从FM到FFM.pdf' P& h8 M& d: N7 x
第3课--排序与CTR预估.pdf1 v* _: H* y$ @5 q6 O. n
京东电商广告和推荐系统的机器学习系统实践.pdf2 s3 ]7 C W: _1 x
腾讯广点通：效果广告中的机器学习技术.pdf' Q# O8 v) K" k4 @4 w
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Kaggle第四课.pdf4 j2 S) R6 ]1 u6 \' {1 `% i" \
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第5课：能源预测与分配问题.pdf
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3 G% p5 c- T7 M8 j' f$ q5 e第7课：推荐与销量预测相关问题.pdf
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. k3 D! B5 z9 \: z5 {+ ?0 M5 X! F% E第8课：金融风控问题.pdf
8 B% v2 L0 |1 ?& W! U' f# |金融风控大赛解决方案.pdf
3 t) Z! [: I) q; J课程附带源码教程课件，教程下载地址：
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发表于 2022-6-9 09:03:02
