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class="recent-post-item"><div class="post_cover left"><a href="/2024/07/08/2024-1-19-%E7%B9%81%E8%8A%B1/" title="繁花"><img class="post-bg" src= "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" data-lazy-src="/../img/cover.jpg" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="繁花"></a></div><div class="recent-post-info"><a class="article-title" href="/2024/07/08/2024-1-19-%E7%B9%81%E8%8A%B1/" title="繁花">繁花</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time class="post-meta-date-created" datetime="2024-07-07T16:04:22.148Z" title="发表于 2024-07-08 00:04:22">2024-07-08</time><span class="article-meta-separator">|</span><i class="fas fa-history"></i><span class="article-meta-label">更新于</span><time class="post-meta-date-updated" datetime="2024-07-07T16:49:35.932Z" title="更新于 2024-07-08 00:49:35">2024-07-08</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%BD%B1%E8%AF%84/">影评</a></span></div><div class="content">繁花 一开始是奔着精彩商战，各方博弈去看的，没想到带给我的却是一层又一层的惊喜和震撼。不管是剧情内容，拍摄手法，镜头语言，角色刻画，演员张力，bgm选曲，我认为繁花都做的极佳，也让我对八九十年代的上海有了更深入的了解。
八九十年代，迎着改革开放的春风，股票，外贸是时代的风口，人们穿行在上海滩的滚滚红尘中，都希望从中分一杯羹，扶摇而上。散户，舰队，麒麟会，再到后面南国投，每一次的新玩法，都象征着市场的迭代升级，也一次次刺激着经济发展。和外资合作，敢拼，敢做，敢摸着石头过河，上的了像至真园般的饭店谈笑风生，下的了深圳一个小县城的工厂里放下身段。饭店吃饭，吃的是合作；一只龙虾，就是一次机会；饭店里的食客，不是在应酬，就是在求人。一切的一切，像极了盖茨比中西方”咆哮的二十年代“。
30年前如此，30年后又有什么变化呢？十几二十年前的房地产，当下的互联网，电商，自媒体，AI…一个又一个时代风口接踵而至。或许你机智聪慧，有创业头脑，又有贵人身旁，成功如宝总；或许你顽强不屈，为争一口气，拼搏如汪小姐；或许你运筹帷幄，有勇有谋，闯荡如李李；或许你后来独立自强，有主张、搞得定、摆得平，输得起如 ...</div></div></div><div class="recent-post-item"><div class="post_cover right"><a href="/2024/07/07/2024-7-7-%E7%88%B1%E5%9C%A8%E9%BB%8E%E6%98%8E%E7%A0%B4%E6%99%93%E5%89%8D%EF%BC%88Before%20Sunrise%EF%BC%89%2075c6bd9af1644fde9c0c1a5c645abb10/" title="爱在黎明破晓前（Before Sunrise）"><img class="post-bg" src= "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" data-lazy-src="/../img/before%20sunrise.png" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="爱在黎明破晓前（Before Sunrise）"></a></div><div class="recent-post-info"><a class="article-title" href="/2024/07/07/2024-7-7-%E7%88%B1%E5%9C%A8%E9%BB%8E%E6%98%8E%E7%A0%B4%E6%99%93%E5%89%8D%EF%BC%88Before%20Sunrise%EF%BC%89%2075c6bd9af1644fde9c0c1a5c645abb10/" title="爱在黎明破晓前（Before Sunrise）">爱在黎明破晓前（Before Sunrise）</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time class="post-meta-date-created" datetime="2024-07-07T15:38:36.540Z" title="发表于 2024-07-07 23:38:36">2024-07-07</time><span class="article-meta-separator">|</span><i class="fas fa-history"></i><span class="article-meta-label">更新于</span><time class="post-meta-date-updated" datetime="2024-07-07T16:51:40.398Z" title="更新于 2024-07-08 00:51:40">2024-07-08</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%BD%B1%E8%AF%84/">影评</a></span></div><div class="content">爱在黎明破晓前（Before Sunrise） 偶然一次逛b站看到的剪辑，翻看评论发现叫爱在三部曲，这是第一部，诞生于1995年，导演是理查德·林克莱特，据说是根据自己在费城的经历拍出的艺术。
影片基本就围绕男女主Jesse and Seline进行，讲述了二人彼此一见钟情，并crazy般的在维也纳度过了afternoon，midnight，sunrise的美丽故事。对于我来说，不得不佩服 Jesse 的勇敢，敢邀请 Seline 打破原计划而和他一起hang out，或许很多人会认为这是因为男主的帅气外表，但我更愿意相信是其幽默健谈、勇敢不羁的人格魅力打动了Seline。
这部影片的拍摄成本非常低，不仅是相较于2024年来说，对比1995年的其它电影亦是如此，但这种简单，纯粹的拍摄手法却更能聚焦观众的注意在二人天马行空的对话中，从小时候的经历到彼此的人格（little boy versus old woman）；从对待手相奶奶的不同态度到彼此的ex-boy/girl friend；从在bus上的的quick talk到唱片店无处安放的情愫；从街边的促膝长谈到饭店幼 ...</div></div></div><div class="recent-post-item"><div class="post_cover left"><a href="/2023/10/28/2023-10-28-%E5%83%8F%E6%A0%91%E4%B8%80%E6%A0%B7%E7%94%9F%E9%95%BF/" title="像树一样生长"><img class="post-bg" src= "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" data-lazy-src="/../img/%E5%83%8F%E6%A0%91%E4%B8%80%E6%A0%B7%E7%94%9F%E9%95%BF.jpg" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="像树一样生长"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/10/28/2023-10-28-%E5%83%8F%E6%A0%91%E4%B8%80%E6%A0%B7%E7%94%9F%E9%95%BF/" title="像树一样生长">像树一样生长</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time class="post-meta-date-created" datetime="2023-10-28T07:03:39.288Z" title="发表于 2023-10-28 15:03:39">2023-10-28</time><span class="article-meta-separator">|</span><i class="fas fa-history"></i><span class="article-meta-label">更新于</span><time class="post-meta-date-updated" datetime="2024-07-07T16:20:15.734Z" title="更新于 2024-07-08 00:20:15">2024-07-08</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E7%94%9F%E6%B4%BB%E5%B0%8F%E6%84%9F%E6%82%9F/">生活小感悟</a></span></div><div class="content">像树一样生长序 作为一个文学水平巅峰停留在初高中的人来说能想要放下手中的ddl来写一些文字可谓极其稀有了，即便如此，我的确是有些东西和感悟要写，算是记录，算是回忆……
一些思考 大学，确实是有些魅力的，它令人着迷的点不仅是你摄入的知识（虽然你科的学生大多数时间都在干这个），还在你接触的人，看到的事。因为贵专业的缘故，其实我并没有接触到什么人，每天做的事也远不如进入大学前幻想的精彩，不过好在，我还是有了些思考。
学业 首先自然是讲讲学业，不知道其它学校或者华科其它专业的本科生教学水平怎么样，但是口口（华科计院）的教学实在不敢恭维，学的东西有用吗，肯定是有用的，但是内容确实也没有紧跟时代，再加上奇怪的时间安排，一门课学下来最后毕业了脑子里剩下的东西并不多。
大多数人只是为了保研出国或者奖学金卷一个高分（羡慕会考试的，我想卷高分都不会），毕业了工作是不是计算机方向都不一定，就算是，大多数技能都是自学，即便你保研了，最终目的只要是就业，无非就是多读3-5年书，拿个研究生博士生的学历，让你在大学的 “温床” 多停留3-5年罢了。那如果留校执教呢，做科研确实是辛 ...</div></div></div><div class="recent-post-item"><div class="post_cover right"><a href="/2023/05/31/2023-5-31-%E7%BB%8F%E5%85%B8%E7%AE%97%E6%B3%95/" title="经典算法"><img class="post-bg" src= "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" data-lazy-src="/../img/cube.jpg" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="经典算法"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/05/31/2023-5-31-%E7%BB%8F%E5%85%B8%E7%AE%97%E6%B3%95/" title="经典算法">经典算法</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time class="post-meta-date-created" datetime="2023-05-31T08:35:05.349Z" title="发表于 2023-05-31 16:35:05">2023-05-31</time><span class="article-meta-separator">|</span><i class="fas fa-history"></i><span class="article-meta-label">更新于</span><time class="post-meta-date-updated" datetime="2024-07-07T16:22:01.984Z" title="更新于 2024-07-08 00:22:01">2024-07-08</time></span></div><div class="content">经典算法插入
直接插入
1234567891011void insertion_sort(int arr[], int len){ for(int i=1; i<len; i++){ int key = arr[i]; //存入当前元素 int j = i-1; while(j>=0 && key<arr[j]){ //后面比前面小 arr[j+1] = arr[j]; j--; } arr[j+1]=key; //否则直接插在后面 }}
折半插入
12345678910111213void BInsertSort(SqList &L){ for(i=2; i<=L.length; ++i){ L.r[0] = L.r[i]; //L.r[i]暂存到L.r[0] low = 1; high = i-1; while(low < high){ m = (high+low) / 2; if(L.r[0].key ...</div></div></div><div class="recent-post-item"><div class="post_cover left"><a href="/2023/05/04/2023-5-4-logistics/" title="logistics"><img class="post-bg" src= "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" data-lazy-src="/../img/beauty.jpg" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="logistics"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/05/04/2023-5-4-logistics/" title="logistics">logistics</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time class="post-meta-date-created" datetime="2023-05-04T07:12:52.270Z" title="发表于 2023-05-04 15:12:52">2023-05-04</time><span class="article-meta-separator">|</span><i class="fas fa-history"></i><span class="article-meta-label">更新于</span><time class="post-meta-date-updated" datetime="2024-07-07T15:56:17.209Z" title="更新于 2024-07-07 23:56:17">2024-07-07</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/AI/">AI</a></span></div><div class="content">==二元分类==输出：标签1/0
img在计算机中保存–>三个矩阵（假设64*64，那么就有3 * 64 * 64个像素，变成特征向量，总维度，也就是矩阵的行为n=3 * 64 * 64，如果有m组训练集，那么矩阵最终为m列，n行)
==logistics回归== y^ 表示 y 等于1的一种可能性或者是机会
w 表示逻辑回归的参数，这也是一个 n 维向量（因为 w 实际上是特征权重，维度与特征向量相同），参数里面还有 b，这是一个实数（表示偏差）
选择使用sigmoid函数原因：如果单纯线性，无法把y^值控制在0-1之间，故取sigmoid(z)
使得z很大，sigmoid(z)趋近1， z 变成一个绝对值很大的负数，sigmoid(z)趋近0
==损失函数==$L(\hat{y},y) = -y\log(\hat{y})-(1-y)\log(1-\hat{y})$ 单次
成本（代价）函数：$J(w,b) = ...</div></div></div><div class="recent-post-item"><div class="post_cover right"><a href="/2023/05/03/2023-5-3-intro%20to%20Deep%20learning/" title="Intro to deep learning"><img class="post-bg" src= "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" data-lazy-src="https://tse3-mm.cn.bing.net/th/id/OIP-C.713XQPQ7LAdyYLOXPI5VcQHaEo?pid=ImgDet&rs=1" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="Intro to deep learning"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/05/03/2023-5-3-intro%20to%20Deep%20learning/" title="Intro to deep learning">Intro to deep learning</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time class="post-meta-date-created" datetime="2023-05-03T11:45:45.673Z" title="发表于 2023-05-03 19:45:45">2023-05-03</time><span class="article-meta-separator">|</span><i class="fas fa-history"></i><span class="article-meta-label">更新于</span><time class="post-meta-date-updated" datetime="2024-07-07T15:57:12.514Z" title="更新于 2024-07-07 23:57:12">2024-07-07</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/AI/">AI</a></span></div><div class="content">==Deep learning==神经网络RELU 修正线性单元
独立神经元叠在一起 –> 神经网络 –> 只需要input x –> output y（中间部分自己完成）
supervised learning 监督学习 ==NN->neural net==
predict房价，ad投放 –> standard NN;
image –> CNN（卷积神经网络）
sequence data==(eg. audio, language)== –> RNN （循环神经网络）
无人驾驶 –> custom, hybrid(复杂)
结构化数据——对数据有很清晰的定义
非结构化数据——相对难解释给计算机
要么神经网络规模大，要么数据量多
data 早期
computation 当下
algorithms 创新算法为了加快计算速度，服务于规模更大的网络
</div></div></div><div class="recent-post-item"><div class="post_cover left"><a href="/2023/04/28/2023-4-28-Kadane%E7%AE%97%E6%B3%95-%E5%8A%A8%E6%80%81%E8%A7%84%E5%88%92/" title="Kadane算法-动态规划"><img class="post-bg" src= "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" data-lazy-src="https://images3.alphacoders.com/841/thumbbig-84199.webp" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="Kadane算法-动态规划"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/04/28/2023-4-28-Kadane%E7%AE%97%E6%B3%95-%E5%8A%A8%E6%80%81%E8%A7%84%E5%88%92/" title="Kadane算法-动态规划">Kadane算法-动态规划</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">发表于</span><time class="post-meta-date-created" datetime="2023-04-28T15:38:00.000Z" title="发表于 2023-04-28 23:38:00">2023-04-28</time><span class="article-meta-separator">|</span><i class="fas fa-history"></i><span class="article-meta-label">更新于</span><time class="post-meta-date-updated" datetime="2023-04-28T15:38:00.000Z" title="更新于 2023-04-28 23:38:00">2023-04-28</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/Algorithm/">Algorithm</a></span></div><div class="content">Kadane算法->动态规划
最大连续子数组和：函数名称是MaxSubArray(L); 初始条件是线性表L已存在且非空，请找出一个具有最大和的连续子数组（子数组最少包含一个元素），操作结果是其最大和；
1234567891011int maxSubArray(int* nums, int numsSize) { int maxSum = nums[0]; int curSum = nums[0]; for (int i = 1; i < numsSize; i++) { curSum = curSum > 0 ? curSum + nums[i] : nums[i]; if (curSum > maxSum) { maxSum = curSum; } } return maxSum;}
链表类似
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