Maybe every program has been tempted to join Google.
However, if you want to "test" success, it will not only test the developer's programming skills, but also test whether the source of the participants' channels is wide, whether the background strength is strong, and whether the brain hole circuit is clear...
However, the dream is to be done, the resume is to vote, and it is not allowed to interview. Therefore, we need to prepare for 10,000 in the interview.
Before the application of the army of thousands of bridges sent back to the Raiders, after the folk programming gods found hidden levels ... it is time to summarize a Google application guide.
PS This strategy is not only for Google (the inspirational brother who has been on the list has been dug up by Amazon~)
Google's technical interview process is a standard for each family.
The interview is known for its strength, and you may want to go home if you look at the problem. These topics are all collected by Glassdoor. However, by the way, the reference answer is also good.
1. Find 1/x.
A: -1/x2
This is the case with Python.
2. Draw a log (x+10) curve.
A: As shown. Just shift the image of logx to the left by 10 squares.
This is the case with Python.
3. How to design a customer satisfaction survey?
A: The third question is so abstract. I don't know where to start, I decided to guide you, you can check in the search engine: "Calculation of customer satisfaction and customer loyalty."
4, a coin toss 10 times, get 8 positive 2 reverse. Is it fair to throw a coin? What is the p value?
5. Pick up the question. 10 coins, each throwing 10 times, what will happen? How to improve in order to make coins more fair?
A: The law of decimals may help you.
Attached a reference: https://medium.com/@lorenz.rumberger/i-think-a-more-advanced-answer-for-the-coin-toss-game-would-use-the-bayesian-method- 569696e89271
6. Explain a non-normal distribution and how to apply it.
A: I don't know how the interviewer is distributed. However, last month MIT published an algorithm that uses the enchanting gamma distribution to help the autopilot system stay in the dark fog.
7. Why use feature selection? If the two predictors are highly correlated, how does the coefficient affect logistic regression? What is the confidence interval for the coefficient?
A: When dealing with high-dimensional data, many models can't be eaten. Feature selection allows us to reduce the dimensionality of the data without losing too much information.
8. K-mean and Gaussian mixture model: What is the difference between K-means algorithm and EM algorithm?
A: CSDN blogger JpHu said that the K-Means algorithm performs "hard allocation" on the clustering of data points, that is, each data point belongs to only a unique cluster; and the MM solution of GMM is based on the posterior probability distribution. The data points are “softly allocatedâ€, that is, each individual Gaussian model contributes to data clustering, but the contribution values ​​are large or small.
Portal: https://blog.csdn.net/TIngyue_/arTIcle/details/70739671
9. When using the Gaussian mixture model, how to judge whether it is applicable or not? (normal distribution)
A: Still, please go to the following page.
10. The label is known when clustering. How to evaluate the performance of the model?
A: CSDN blogger Howhigh said that if there is a category tag, the clustering result can also calculate the accuracy and recall rate as the classification. However, classification labels should not be used as an evaluation indicator for clustering results, unless you have relevant prior knowledge or some assumptions, knowing that the gaps within this classification category are smaller –
11, why not use logical regression, but use GBM?
A: GB is Gradient BoosTIng. Quoting the words of Frankenstein, from the decision boundary, the decision boundary of linear regression is a straight line, the decision boundary of logistic regression is a curve, and the decision boundary of GBM may be many lines.
Logistic regression can only deal with regression problems, and GBM can also be used to solve classification or sorting problems.
Reference answer portal:
Https://TIon/54626685/answer/140610056
12. How many people apply for Google each year?
A: Two million. Most people may just just cast aside and see if they will win.
Of course, the technical questions are endless, and they can't be answered. The following unified questions are not given. Please conduct self-test and pay attention to the test time.
13. You made some changes to a Google APP. How to test whether an indicator has increased
14. Describe the flow of data analysis.
15. In the Gaussian Mixture Model (GMM), derive the equation.
16, how to measure the user's love for video?
17. Simulate a binary normal distribution.
18. Find the variance of a distribution.
19. How to establish a median Estimator?
20. If the two coefficients in the regression model are estimated to be statistically significant, will the two be tested together, will it be equally significant?
Not just technologyIn addition to these profound technical issues, Google’s interviews over the years have always had some mysterious questions that directly hit the soul. BI also counts some, for example:
How many golf balls can I put in a school bus?
How much does it cost to wipe through all the windows in Seattle?
Why is the manhole cover round?
Another long one:
You only have two raw eggs, which are extremely strong and extremely fragile eggs. In the high-rise building of the 100-story building, before the two eggs are killed, how can we know that they can fall from the floor to the top? How many steps do you need?
Eggs indicate:
Very curious, how is the brain hole question scored. Friendly reminder: Some of the above questions, some of them can be shaken...
If you want to know the answer and more similar questions, you can reply to the word "mystery" in the quiz public address (ID: QbitAI) dialogue interface.
The most orthodox Google interview book in historyThe real question is over. Although interview preparation is a commonplace topic, the following book will look at you anyway.
On the "blood system", this collection is the most authentic, because it is specially prepared for the "Future Googler" on the Google Recruitment website. Let’s take a look at what the recruiter has personally made to the interviewer –
Predictive interview questions: Before the interview, you can basically predict 90% of the problems. "Why do you want to apply for this job?" "What problems have you solved?" These questions are basically in the interview, and it is helpful to write 20 out in advance.
Plan: After writing the most likely problems, write down your answers to each of the questions on your list. This will help you to deepen your impression of these issues and is a good tool for answering questions during the interview.
Plan B&C: For these questions, Google recruiters suggest that you better prepare three answers. These alternate answers can help you conquer the next interviewer when the first interviewer doesn't like your story.
Explanation: The interviewer wants to understand your thoughts, so you need to show your thinking process and the final solution during the interview process. This section is not only evaluating your technical skills, but also assessing your flexibility to solve problems.
Storytelling: Google interviewers hope to "tell a story." There is a very interesting interview tip, that is, each question should be answered with a story. For example, the question "How do you lead..." is best to tell a story.
Discussion: During the interview process, you may not consciously enter some “trapsâ€. This is the interviewer who wants to know in depth what information you value when you encounter technical problems, and hope to see how you handle this problem and how to solve the problem. The main method, then you must discuss your thinking process.
Improvement: Think about how to improve your current solution and let the interviewer know what you are doing and why.
Exercise: The final candidate should always remember that practice makes perfect. Simulate the interview session and confidently say your answer until you can tell each story clearly and concisely.
It seems that preparing for Google's interview is a time to live. In addition to the technical ability to be excellent, the preparation of these 20×3 questions in the interview alone has to be prepared for a lot of time.
By the way, the Google engineers who have already applied for success have also provided you with some "preparation" suggestions for technical problems, listening to the old sayings, and helping you with your interview.
Yes, there are hidden levels!
The only way to apply for Google is by interpolating, school recruiting, and sending resumes. Naive, looking at the brains of Google engineers, according to a number of great gods revealed on the blog, Google's application sources also have secret channels.
If Google captures that you are searching for a particular programming term, someone may invite you to apply for the position. Someone can unlock this hidden level~
Little brother Max Rosett has encountered an interesting story. When searching for "Python lambda function list parsing" with Google, the search interface splits and collapses backwards. A box pops up saying "You are using our voice" and invites him to challenge.
After clicking on "Challenge", the page jumps to a page called "foo.bar" and a time-limited challenge will appear. After successively breaking through six questions, foo.bar invited the challenger to submit personal information. Later, there were recruiters to come to the resume.
The address of this foo.bar is as follows:
Https://
However, I am excited, I have no way to register without the invitation of Google.
The revelation of the end of the story may be more than Google search...
Google-style "high school entrance examination"Regarding the Google interview, its popularity and difficulty are no different from the "high school entrance examination" in the industry. The scene of the thousand-armed horse crossing the single-wood bridge has appeared again.
One of them wants to work in Google, "Inspirational Brother" John Washam fires. This little brother is studying economics at the university. After he retired from the army, he went to teach English, but the desire for code and Google has not been erased. He is inspirational. Eight months to prepare for a full-time Google interview to achieve your goals!
â–³ "Inspirational Brother" John Washam
This is an "ascetic" style of practice. The younger brother has studied 1000 pages of C++ books in three weeks, and has harvested more than 21,000 stars on GitHub. He also made 1,792 electronic cards for review... reading, writing code and The time spent listening to the lectures was more than 1,000 hours.
â–³Inspirational brother's summer reading list is only a small part of the preparation process
After eight months of hard preparation, the younger brother... was still unsuccessful, and even the telephone interview was not directly rejected.
But the effort will always pay off. After being rejected, the younger brother is currently working for Amazon.
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