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(資料整理中)

iThome 鐵人賽 2025

快速掌握資料結構與演算法

天數	標題	連結
Day 1	(Day 1) 介紹與準備	Blog / iThome
Day 2	(Day 2) 陣列 (Array)	Blog / iThome
Day 3	(Day 3) 矩陣 (Matrix)	Blog / iThome
Day 4	(Day 4) 鏈表 (Linked List)	Blog / iThome
Day 5	(Day 5) 堆疊 (Stack)	Blog / iThome
Day 6	(Day 6) 隊列 (Queue)	Blog / iThome
Day 7	(Day 7) 二元樹 (Binary Tree)	Blog / iThome
Day 8	(Day 8) 平衡樹 (Balanced Tree)	Blog / iThome
Day 9	(Day 9) 其他樹 (Other Trees)	Blog / iThome
Day 10	(Day 10) 圖 (Graph)	Blog / iThome
Day 11	(Day 11) 演算法評估 (Algorithm Analysis)	Blog / iThome
Day 12	(Day 12) 氣泡排序 (Bubble Sort)	Blog / iThome
Day 13	(Day 13) 選擇排序 (Selection Sort)	Blog / iThome
Day 14	(Day 14) 插入排序 (Insertion Sort)	Blog / iThome
Day 15	(Day 15) 基礎排序演算法比較	Blog / iThome
Day 16	(Day 16) 二元搜尋 (Binary Search)	Blog / iThome
Day 17	(Day 17) 內插搜尋 (Interpolation Search)	Blog / iThome
Day 18	(Day 18) 分治法 (Divide and Conquer)	Blog / iThome
Day 19	(Day 19) 動態規劃 (Dynamic Programming)	Blog / iThome
Day 20	(Day 20) 貪婪演算法 (Greedy Algorithm)	Blog / iThome
Day 21	(Day 21) 圖演算法 (Graph Algorithm)	Blog / iThome
Day 22	(Day 22) Dijkstra 最短路徑演算法 (Dijkstra’s Algorithm)	Blog / iThome
Day 23	(Day 23) Bellman-Ford 演算法	Blog / iThome
Day 24	(Day 24) Floyd-Warshall 演算法	Blog / iThome
Day 25	(Day 25) A* 搜尋演算法 (A-star Search)	Blog / iThome
Day 26	(Day 26) 最小生成樹 (Minimum Spanning Tree)	Blog / iThome

30 天入門常見的機器學習演算法

天數	標題	連結
Day 1	(Day 1) 介紹與準備	Blog / iThome
Day 2	(Day 2) 線性迴歸 (Linear Regression)	Blog / iThome
Day 3	(Day 3) 多項式迴歸 (Polynomial Regression)	Blog / iThome
Day 4	(Day 4) 正規化迴歸 (Regularization Regression)	Blog / iThome
Day 5	(Day 5) 邏輯迴歸 (Logistic Regression)	Blog / iThome
Day 6	(Day 6) 邏輯迴歸 (多項式 + 正規化)	Blog / iThome
Day 7	(Day 7) 回顧迴歸：從線性邏輯到學習本質	Blog / iThome
Day 8	(Day 8) K-近鄰 (K-Nearest Neighbors)	Blog / iThome
Day 9	(Day 9) 樸素貝氏分類器 (Naive Bayes Classifier)	Blog / iThome
Day 10	(Day 10) 支援向量機 (Support Vector Machine)	Blog / iThome
Day 11	(Day 11) 二元分類任務驗證指標	Blog / iThome
Day 12	(Day 12) 多元分類任務驗證指標	Blog / iThome
Day 13	(Day 13) 迴歸任務驗證指標	Blog / iThome
Day 14	(Day 14) 決策樹 (Decision Tree)	Blog / iThome
Day 15	(Day 15) 隨機森林 (Random Forest)	Blog / iThome
Day 16	(Day 16) K-Means	Blog / iThome
Day 17	(Day 17) 淺談深度學習 (Deep Learning)	Blog / iThome
Day 18	(Day 18) 全連接神經網絡 (Fully Connected Neural Network)	Blog / iThome
Day 19	(Day 19) 神經元 (Neuron)	Blog / iThome
Day 20	(Day 20) 激活函數 (Activation Function)	Blog / iThome
Day 21	(Day 21) 卷積神經網絡 (Convolutional Neural Network)	Blog / iThome
Day 22	(Day 22) 深度學習中的正規化與正則化 (Regularization in Deep Learning)	Blog / iThome
Day 23	(Day 23) 深度學習中的優化方法 (Optimization in Deep Learning)	Blog / iThome
Day 24	(Day 24) Adam 優化器 (Adaptive Moment Estimation)	Blog / iThome
Day 25	(Day 25) 循環神經網路 (Recurrent Neural Network)	Blog / iThome
Day 26	(Day 26) 長短期記憶 (Long Short-Term Memory)	Blog / iThome
Day 27	(Day 27) 閘控循環單元 (Gated Recurrent Unit)	Blog / iThome
Day 28	(Day 28) Seq2Seq (Encoder Decoder with RNN, LSTM, GRU)	Blog / iThome
Day 29	(Day 29) 注意力機制 (Attention Mechanism)	Blog / iThome
Day 30	(Day 30) 系列結尾	Blog / iThome