p**r
发帖数: 5853 | 1 各位大神大牛可以指点指点简历怎么改，
我一般一张纸覆盖大概。
然后附一份做过的项目目录时间，大概500+
以下纯粹话痨，无聊的继续，不然赶紧去刷题。
因为家里村里没人，吃不上大米饭，所以大二就出道了，
后来为了追白富美，白天端盘，晚上洗碗的赚钱，
现在为了养小白富美，白天杀老鼠，晚上刷试管，
导致做了从通下水道到装马桶的各种项目。
基本就是给钱就干，要啥姿势就啥姿势，
并且长期学习四大名妓flag的及ua等当红新妓的姿势，
并且加以揣摩改进，现在自我感觉骚气横竖都溢，
所以鼓起勇气前往flag选秀，希望能进入四大妓院成为一代名妓。 | n*****n
发帖数: 1 | 2 First Last
[email protected]
+86 130 0000 0000
Beijing, China
Work Experience
Miaozhen System, Machine Learning Engineer, Beijing 2019.02 - 2019.05
●Worked at advertisement traffic anti-cheating algorithm team, processed 2
billions of data daily, produced half million extra revenue for the company
● Decrypt the MD5 encrypted logs and improved the current algorithms
accuracy from 60% to 63%
● Implemented a rule based algorithm which is counting the data as invalid
traffic (IVT) with same cookies but different IDFA, IMEI, MAC using java,
Hadoop, Map Reduce, Distributed Computing on Linux Server
Microsoft, Azure, Software Engineer, Seattle 2018.02 - 2018.04
● Used EDA to analyze the malicious software data, selected features and
predict using XGBoost
● Familiarized the Internal Offices Tools such as Skype, OneDrive, OneNote,
Teams
● Read Azure official documents and get known the server deployments and
services provided
Education
US Public School
Master of Science, Computer Science, Statistics
● Relevant Course: Machine Learning, Artificial Intelligence, Data Mining,
Pattern Recognition, Database Management, Big Data Analytics and Text Mining
, Data Structure and Algorithm, Computational Geometry, Regression,
Interpretation of Data
China Regular University
Bachelor of Science, Finance, Ranking: 1/200
● C/C++, Calculus I & II, Linear Algebra, Probability, Java - Object
Oriented Programing, Discrete Mathematics, Operating System,
Computer Networks, Partial Derivative Equation
Skills
● Professional: Java, Python, C/C++, Hadoop, Linux, R, Github, Git, Qt,
Sublime, Pycharm, Eclipse
● Familiar: SQL, Scala, Spark, Objective-C, AWS, Apache Hive, Mongodb,
MySQL, Excel
● Machine Learning : Scikit-Learn, Tensorflow, Caffee, Keras, Theano, Torch
, mxnet, DeepLearning4J
Projects
Survival Analysis of Titanic
● Did Exploratory Data Analysis to data including Histogram, Pie Chart, and
Probabilistic Statistics
● Used Feature Engineering to fix the missing data, transformed the data
format to fit the model
● Implemented Logistics Regression, Random Forest, GBDT and XGBoost,
achieved 90% accuracy
A Movie Recommendation System Based on Collaborative Filtering
● Achieved a mean squared error rate of 0.944
● Collected data from MovieLens and predicted users’ rating on certain
movies
● Used Pearson Correlation Similarity Measure to cluster users as
collaborative filtering
● Applied both K-means and category to cluster movies and compared results
of different clustering
Image and Digits Classification based on Naive Bayes and Perceptron
Classifier
● Extracted features from handwritten digits and face pictures and convert
it into zero-one matrix
● Estimated parameters such as prior and posteriors from training data
● Used Naive Bayes and Laplace smoothing achieved accuracy rate of 84%
● Implemented Perceptron algorithm to classify digits and face pictures,
achieved 97% accuracy
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发帖数: 1054 | 3 The median of the annual total compensation of all of our employees (other
than Mr. Merritt), including our consolidated subsidiaries, was
approximately $261,231. This annual total compensation is calculated in
accordance with Item 402(c)(2)(x) of Regulation S-K, and reflects, among
other things, salary and bonus earned and aggregate “grant date fair value
” of RSU awards granted during the 12-month period ended January 31, 2019. |
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