Data Science Nyumon Senkei Daisu Kakuritsu Kara Suri Saiteki Ka Made
Harada Fumiko / Cho Shimakawa Hiromitsu / Cho
| Points You Earn | 1% (42p) |
|---|---|
| Release Date | late September 2023 |
| Availability | In Stock at Supplier:Usually ships in 2-4 days |
Product Details
| Catalog No. | NEOBK-2904044 |
|---|---|
| JAN/ISBN | 9784320125650 |
| Product Type | BOOK |
| Pages | 410 |
|---|
Books are basically written in Japanese except for bilingual books or ones indicated as not written only in Japanese.
Description in Japanese
データサイエンス入門 線形代数・確率から数理最適化まで / 原田史子/著 島川博光/著
Related Offer & Feature
Tracklisting
| 1 |
ベクトル
|
| 2 |
要約統計量と相関
|
| 3 |
無相関検定
|
| 4 |
協調フィルタリング
|
| 5 |
クラスター分析
|
| 6 |
最適化問題と求解法
|
| 7 |
行列―1次変換、特に直交変換
|
| 8 |
Geam‐Schmidtの直交化技法と直交分解
|
| 9 |
非負値行列分解
|
| 10 |
行列式
|
| 11 |
回帰分析
|
| 12 |
固有値と固有ベクトル
|
| 13 |
主成分分析
|
| 14 |
因子分析
|
| 15 |
PageRankアルゴリズム
|
| 16 |
判別分析
|
| 17 |
林の数量化理論と数量化1類
|
| 18 |
数量化2類
|
| 19 |
数量化3類
|
| 20 |
数量化4類
|
| 21 |
確率変数による記述
|
| 22 |
機械学習の概要
|
| 23 |
決定木と集団学習
|
| 24 |
ロジスティック回帰
|
| 25 |
混合Gaussモデルによるクラスタリング
|
| 26 |
ニューラルネットワーク
|
| 27 |
不等式制約付き問題の最適性
|
| 28 |
サポートベクトルマシン
|
| 29 |
隠れマルコフモデル
|
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