Alex Tech Bolg-CSDN博客

原创 Roadmap - Backend

Internet, TCP/IP, SSL/TLS,

2023-10-24 04:19:42 425

原创 Prompt Engineering

Principles:2. Give the model time to think.

2023-10-02 05:30:14 388

Agile development: Make you won’t do extra workSprintProduct Backlog:User StoryTimeboxingSprint Planning MeetingSprint Review Meeting: deliverablesRetrospective meeting:Daily meeting:KISS: Keep it simple, stupid!Treat warnings as errors

2023-09-19 22:43:35 266

原创 HTML-CSS-js教程

双标签单标签html5的DOCTYPE声明用于定义文档的头部。文档的头部包含了各种属性和信息，包括文档的标题，在Web中的位置以及和其他文档的关系等。绝大多数文档头部包含的数据都不会真正作为内容显示给读者定义文档的主体，包含文档的所有内容，在页面中显示出来，用户可以直接看到的内容定义文档的标题，可以显示在浏览器的标签栏或状态栏上。标签是标签中唯一必须要求包含的东西，就是说head一定要写title，用来描述HTML网页文档的属性，关键词等。例如。

2023-02-10 11:49:23 624 1

原创词嵌入和交叉熵｜Word Embedding and Cross Entropy

词嵌入，交叉熵损失函数，Word Embedding，Cross Entropy，Pytorch

2022-10-28 12:32:04 649

原创 Transformer和BERT学习笔记｜Notes for BERT and Transformer

对每一个下游任务，构造一个跟这个任务相关的神经网络，将于训练好的表示，如词嵌入，作为一个额外的特征，和本来任务的输入一起输入到模型中。我希望这些特征已经有了比较好的表示，所以导致模型训练起来比较容易这两个途径都是使用一个相同的目标函数：都是使用语言模型，并且是单向的（unidirectional language models）Bert 的改进：Masked Language model。

2022-10-12 20:32:43 532

原创代理标签的半监督学习算法｜Proxy-label Approaches for Semi-supervised Learning

Tri-training with disagreement 在原算法基础上做了个小调整（算法2Co-training中的第8行），要求对于模型。应该拒绝预测，也就是disagreement。置信度较高的样本，第三个模型。

2022-10-11 11:48:37 340

原创自然语言处理教程-注意力模型｜Natural Language Processing with Attention Models

NLP，Transformer，Bert

2022-10-07 06:15:39 412

原创应用深度学习课程笔记｜Review of 4995 Applied Deep Learning

Deep Dream里面能够改变的参数不是filter，而是input image，通过调整input image，来使得output image as high as possible (excites the layer)大部分的参数来自于最后一层dense layer，通过global average pooling可以极大减少参数数量。

2022-09-26 11:02:47 612

原创数据科学AWS实践1-AutoML｜Analyze Datasets and Train ML models using AutoML

AWS, AutoML, Sagemaker, S3, Autopilot

2022-08-19 01:24:58 263 1

原创 Git常用语句｜Git command tutorial

Git

2022-07-30 06:07:28 150

原创前端网络框架Bootstrap教程｜Front-End Web UI Frameworks and Tools: Bootstrap4

前端，Front end，Bootstrap，JavaScript

2022-07-27 03:23:25 231

原创吴恩达深度学习笔记3｜Coursera Deep learning Notes - Structuring Machine Learning Projects

Deep learning, 吴恩达深度学习教程笔记

2022-07-25 00:34:43 209

原创可解释机器学习- InterpretML的使用｜interpretable machine learning- InterpretML tutorial

可解释机器学习，InterpretML

2022-07-15 11:49:13 1642

原创可解释机器学习- LIME模型讲解｜interpretable machine learning-LIME

可解释机器学习，interpretable machine learning，LIME，模型讲解

2022-07-15 11:47:08 3871

原创 Python中的多进程多线程｜Multiprocessing and Multithreading in Python

进程，线程，多进程，多线程，一些concurrent package的实例

2022-07-12 21:48:02 720

原创吴恩达深度学习笔记及作业答案｜Coursera Deep learning Notes - Improving Deep Neural Networks

Deep learning, dropout (inverted dropout), Early stopping, normalization, Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

2022-07-12 04:33:08 2349

原创 Review of 4705 NLP

ContentsLecture 12: Lexical Semantics (part I) - Word Representations and Word Embeddings.Lecture 13: Machine Learning: Linear and Log-Linear ModelsLecture 14: Machine Learning: Feed-forward Neural Networks, Autoencoders/embeddings, Dense networksAutoencod

2022-05-10 12:45:59 137

原创 Review of 4121 Computer System for Data Science

ContentsComputer systems and performance rules of thumbData centersDatabasesStorage and distributed file systemsDistributed systemsMapreduceDistributed analytics and streamingCachingAdditional informationComputer systems and performance rules of thumbLa

2022-04-24 08:57:40 439

原创 Review of 4721 Machine Learning

ContentsMultivariate GaussiansReview: Variance and covarianceMultivariate GaussiansPCA/ SVDMultivariate GaussiansReview: Variance and covarianceCovariance matrix: X⃗=(X1,X2,…,Xd)\vec{X} = (X_1, X_2, \dots, X_d)X=(X1,X2,…,Xd), cov(X⃗)cov(\vec{X})cov

2022-04-21 09:38:22 1423

原创 Review of Linear Algebra

ContentsTranspose and Inverse(AB)−1=B−1A−1(AB)^{-1} = B^{-1} A^{-1} (AB)−1=B−1A−1(AT)−1=(A−1)T(A^T)^{-1} = (A^{-1})^{T}(AT)−1=(A−1)TAA−1=I, (A−1)T(AT)=IAA^{-1} = I,\ (A^{-1})^T(A^T) = I AA−1=I, (A−1)T(AT)=IPermutation matrixP−1=PT P^{-1} =

2022-04-07 12:01:17 313

原创 Review - 5703 Statistical Inference and Modeling

ContentLecture 1 IntroLecture 2 EstimationEstimation:Two estimation methodsOptimality in estimationLecture 3 Confidence intervals and hypothesis testingLecture 1 IntroLLN (Law of large numbers)CLT (Central Limit Theorem)CMT (Continuous Mapping Theorem

2022-02-08 04:06:28 689

原创 Review of 4246 Algorithms for Data Science

ContentsImportant algorithmsNoteLecture1: Insertion sort, efficient algorithmLecture2: Merge sortLecture3: Binary search, quicksortLecture5: Graphs, Breadth-First Search (BFS)Lecture6: Depth-first search, topological sortingLecture7&8: Strongly connect

2021-12-28 00:40:38 370

原创 Cracking Metric/Business Case/Product Sense Problems

Table of contents1. What are product sense/business case/metric problems2. 3 categories of questions and frameworks2-1 Diagnose a problem2-2 Measure success2-3 Launch or not1. What are product sense/business case/metric problems2. 3 categories of ques

2021-12-04 06:21:20 124

原创 Product Case Interviews

Table of contentsTipsIt's okay to make mistakes.Interact with the interviewerAlways clarify questionsAsk time to structure your communicationRed flagYou have no idea at allYou have to many ideasFollowing Frameworks BlindlyNot able to defend your selfFacebo

2021-12-04 01:48:04 297

原创 Summary of Statistics for Interview

Table of ContentsP_valuePower of a test / statistical powerP_valuehttps://en.wikipedia.org/wiki/P-valueIn null hypothesis significance testing, the p-value is the probability of obtaining test results at least as extreme as the results actually observ

2021-11-15 07:40:41 466

原创 SQL刷题总结 SQL Leetcode Review

Table of contentsnull, '', 0null, ‘’, 0这三个值是不同的。对于0，直接用=检查即可。对于“”，也可以直接用=检查。但是需要注意的是，0 = ‘’是成立的。所以需要单独删除0的情况。eg: 176with temp as ( select distinct salary, dense_rank() over(order by salary desc) as r from Employee)select IF( (select t

2021-11-09 04:11:19 731 1

原创 AB Testing Review

Cracking A/B Testing Problems in DS interviewhttps://towardsdatascience.com/7-a-b-testing-questions-and-answers-in-data-science-interviews-eee6428a8b63power = 1 - (Type 2 error)More samples if sample variance is larger.Less samples if differen

2021-11-04 10:00:01 281

原创 Hypothesis testing

Example of proportion1 ProportionExperiment: test color color of a buttonClick through probability: N(users who clicked) / N(total users)1000 users in both control and treatment groupsResults:Control group: 1.1% CTPTreatment group: 2.3% CTPSign

2021-11-04 04:17:35 523

原创 reduce/map/combination/permutation - itertools Python example 常用python itertools 函数

Table of ContentsMap/ Reducecombination/ permutationMap/ Reducefrom functools import reducecombination/ permutationIf we want to input parameterlist(map(lambda s: list(combinations(s, 2)), edge_lst))

2021-11-02 12:27:04 110

原创 Review 4995 Applied Machine Learning

Table of contentsLecture 1Basic conceptExploratory Data Analysis & VisualizationLecture 2Supervised Learningk-nearest neighborsDevelopment-test splitRandom SplittingStratified SplittingStructured SplittingHyperparameter tuningModel selectionModel selec

2021-10-27 12:17:15 380

原创 Machine Learning Review Note

目录Bagging, Boosting, StackingTF-IDFBagging, Boosting, Stackinghttps://towardsdatascience.com/ensemble-methods-bagging-boosting-and-stacking-c9214a10a205https://zhuanlan.zhihu.com/p/36822575The main hypothesis is that when weak models are correctl

2021-09-23 01:30:43 1298

原创【量化笔记】波动volatility相关技术指标以其含义

目录Average True Range (ATR)计算操作Bollinger Bands计算操作Bollinger BandWidth%BUlcer Index计算Average True Range (ATR)参考：https://www.thebalance.com/how-average-true-range-atr-can-improve-trading-4154923https://school.stockcharts.com/doku.php?id=technical_indicator

2021-06-10 18:08:47 2495 1

原创【量化笔记】动量Momentum相关技术指标以其含义

目录Awesome Oscillator (AO)计算Kaufman's Adaptive Moving Average (KAMA)计算Step 1: Efficiency Ratio (ER)Step 2: Smoothing Constant (SC)Step 3: KAMAPercentage Price Oscillator (PPO)计算Percentage Volume Oscillator (PVO)Rate-of-Change (ROC)Relative Strength Index (R

2021-06-05 16:43:57 2201

Video_Games.csv

https://raw.githubusercontent.com/selva86/datasets/master/a10.csv

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