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Sunday, January 29, 2017

12 Silicon Valley Tech Startup Job Search Tips


  1. Indicate on Linkedin that you are an available candidate, a service offered by their premium plan
  2. Consider having a portfolio, works and arts to show rather than just a resume
  3. Previous startup experience is a huge plus. Startup founders and teams look for like minded people who can hustle and deal with the startup crunch
  4. Check the job board for alumni offered by your university. 
  5. Google and read information about the company on the internet. Any info on the internet is fair game in the interview process.
  6. Prepare for phone screening interviews with recruiters. Sometimes these calls are scheduled quickly after resume submission when a position needs to be fulfilled.
  7. Be ready for coding and technical interviews over the phone. Silicon Valley is tech savy even recruiters known how to ask a technical question or two.
  8. Brush up on software and web based technical skills. Silicon valley is very software heavy except for Apple and a few other places.
  9. If you are applying for an data analyst job, be prepared to be interviewed like a junior data scientist. Even the business roles can be technical in nature.
  10. Use new job sites such as White Truffle, Hired, Muse ... in addition to traditional sites like Linkedin, job boards etc.
  11. Take an advanced online course to brush up your skills or learn cutting edge technology such as self driving car on Udacity.
  12. Research the technical stack used by the startup

Machine Learning Resources: Stanford Youtube Machine Learning by Andrew Ng

All of Stanford's machine learning course by Andrew Ng (not the coursera version) is posted on Youtube. Here's the course material site: http://cs229.stanford.edu/ and here's the video playlist https://www.youtube.com/watch?v=UzxYlbK2c7E&list=PLA89DCFA6ADACE599 This lecture series is a full-version academic course on Machine Learning that has and is Stanford University rigor. Its machine learning slides can be found here http://cs229.stanford.edu/materials.html

Hugo Barra Googler Xiaomi VP Joins Facebook VR - Startup News

Hugo Barra once a senior Googler, Xiaomi global VP will join Facebook VR and leads all Facebook VR efforts.

After spending years at Google and rumored to had been ousted due to personal and leadership differences with the Google founders, Hugo Barra had spent many years building Xiaomi under founder Leijun in China. Xiaomi has since then developed many hardware products, viral phone strategies and expanded to India.

Hugo will lead and shape the vision of Oculus VR at Facebook. He may not be as famous as Steve Jobs, but he essentially is one of the most experienced super tech product manager and leader in the Silicon Valley and the world. Facebook will need his experience scaling giant tech companies as well as dealing with China, a market that Facebook's founder Mark Zuckerberg has been courting.

iOS prototyping design tool: prototyping notepad

Google UX UI prototyping design team and many silicon valley startups use paper prototyping tools such as this iOS screen real estate user flow notepad.

Saturday, January 28, 2017

Machine Learning Stanford on Youtube Lecture 02 Notes



  • Agenda: linear regression, gradient descent and normal equations
  • Machine learning notations and conventions
Note this is not the coursera course. This is the long youtube version of the Stanford.

Seth Godin Marketing Wisdom quote on story telling

Seth Godin marketing class on skillshare bestselling author in business and marketing.  Growth hacking marketing tips and quotes by Seth Godin.
"
Marketing and advertising were the same thing, but going forward that's not what marketing is. 

Marketing is the act of telling a story to people who want to hear it, making that story so vivid so true, that people who hear it tell other people.
"

Reaching Level 30 on Pokemon GO: get lots of items


Items you can receive upon reaching level 30. 30 ultra balls, 20 max potion, 20 max revive, 20 razz berry, 3 incense, 3 lucky egg, 3 egg incubator, 3 lure module

Monetize WordPress How to add adsense to free WordPress site


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How to add google adsense ad to free wordpress site, meaning a website that is not advanced hosted wordpress or custom domain. It used to easy: simply generate an ad unit in adsense, copy and paste the code to WordPress layout sidebar widget, text widget. It no longer works. You will have to subscribe to the $8 dollar premium plan to use WordAd. To monetize your WordPress site, you will now have to pay for a premium plan. Keep in mind you want to reach a small critical mass of audience on your blog before you can monetize your blog and only then does it make monetary sense to monetize your site. 

Tuesday, January 24, 2017

It's real google will pay you to do what you love - monetize your blog and YouTube channel


Monetize your blog and YouTube channel

It's true it's real google will actually pay you to do what you love the most. I have been blogging about learning to code, japan, and Pokémon GO and I just got paid by google - my first ad revenue is real and in the bank. How did I do it?


  • Write about what you love. Your niche may be small but the authenticity of your writing, opinions and details make a huge difference. My blog audience is small, like in the hundreds and thousands but because my posts are relevant users end up enjoying the ads they are served (udacity, amazon web services). Despite not being able to earn much from CPM (based on 1000s impression), my blog's click through rare is high. CPC is a valuable earning 
  • Be detail oriented. I am no internet sensation, I am not viral. How do I deliver value to my readers? By being thorough and detailed in my presentation of observations and the follow up analyses.
  • Be compliant be 100% compliant. When Google Adsense first came out, I was young and had an account that I played with. I tested my site and clicked on the ads and was blocked forever. I probably can contact them to unblock because it has been 10 years but the reality is grim Google is hard to reach and bans are permanent to deter opportunists. They really mean it. If you are not compliant, displayed fraudulent info, violated copy right content on YouTube, click on your own ads Google's algorithm will find you and terminate your entire account and stop monetization on all channels. Google's algorithm has proven to be intelligent (machine learning), complex (deep learning) and capable ( big data). You will be caught. 
  • Follow a schedule. Smartly timed intervals of updates is desirable. No one wants to be overwhelmed by spam or visit your site or channel and find nothing new 3 times in a row
  • Have a brand or a style. All successful viral influencers have a brand or a style that is extremely distinctive. Think Justin Bieber, he has a very specific hair cut and look, and he only sings certain cheesy songs. But that makes him extremely recognizable. Bread girl on Instagram has a repeatable viral machine : putting her face in different types of bread. While the safety and the usefulness of such an act is questionable, its success is very repeatable. It's a machine! We may not have that money making machine but we can think and design our brand message. For me, this blog is about Silicon Valley tech lifestyle so it has gadgets, Silicon Valley jobs, startup tax and logistics. I cannot post food recipes here unless it is about how to make a Star Wars cake. Clam chowder is irrelevant here and will make my readers question my blog. It's 
  • Analyze what works. My Pokémon GO posts on blogger generate thousands of views but no one watch my YouTube Pokémon GO videos. So I have to post more Pokémon on the blog and focus more on learn to code tutorials on my YouTube channel. Find what works, optimize and then repeat success make it better

Friday, January 20, 2017

Machine Learning code pattern 01

Code pattern 01 numpy use array().T to get matrix transpose

Example:

X = [1,2,3]
XT = array(X).T


Machine Learning Concepts 01

 There are three main machine learning styles:


  1.  Supervised learning 
  2.  Unsupervised learning
  3.  Reninforcement learning

Wednesday, January 18, 2017

Udacity Machine learning Nanodegree Syllabus and Summary

udacity nanodegree - becoming a machine learning engineer. This is my personal notes summarizing what I learned from the section, consider it my personal study notes. The part I labeled syllabus is the actual outline of the course (e.g. I try to use section title as the syllabus section title)

Section supervised learning
Sub section artificial neutral networks
Sub section neural networks
     how does a neuron work (illustrated)
     How artificial neural network works (illustrated) perceptron
     A group of inputs, each with a weights, processed by the network and output 1 of and only if a preconfigured threshold is met
     Artificial neural networks can be tuned

  • Think of inputs as signals with different strengths, weights as sensitivity to those strengths. Can be tuned and adjusted to computer variety of tasks. Hence a collection of perceptroncomputing units is powerful
  • The weights sum of all the inputs is called the activation
  • When activation is greater than the threshold theta the perceptron outputs 1

Friday, January 13, 2017

Data Science for Business by Provost Fawcett data science book review


  • Interesting business approach to understand and apply data science
  • Use verbose texts when explaining simple concepts
  • Introduce advanced concepts like Information Gain and Entropy early in the book pg51. Less accessible for beginners. Good for people preparing for interviews and people who already got an introduction to machine learning
  • Writes the full formula out, avoid using sigma notation to make it more accessible for business readers
  • Useful graph of entropy pg 52
  • Helpful graphical illustration pg54-pg55 two trees with different information gain
  • The learning curve is not a slowly ascending one. The topics jump around in this book
  • Variance measures impurity pg56

Thursday, January 12, 2017

Udacity Machine Learning Nanodegree Linear Regression sample code

from sklearn import linear_model

reg = linear_model.LinearRegression()
reg.coef_
reg.intercept_

Codecademy SQL Table Transformation Subqueries Walkthrough


  • 1. Table Transformation
    • SELECT * FROM flights WHERE (SELECT code FROM airports WHERE elevation < 2000); 
    • Nested subqueries 
    • First get all the codes from airports table if its elevation is smaller than 2000
    • Use this as a filter to query all columns of data from the flights table
    • Don't forget the ; semicolon in the end

Friday, January 6, 2017

Udacity Year in Review

Udacity online course highlighted itssuccesses and milestones in 2016. 
  • Udacity currently offers 159 courses
  • Udacity's site-wide busiest time for learning is the Month of October
  • Student watched the Developing Android Apps video by Google the most
  • Read the full article here Udacity 2016 Year in Review

Udacity Machine Learning Engineer Nanodegree - skills you will learn

  • Sklearn python machine learning library
  • Jupyter Notebook
  • Panda

You will not spend too much time on the following, so please review, study, before proceeding to the course:
  • Reviewing linear algebra 
  • Reviewing probability
  • Reviewing statistics

Udacity Intensive Connect Data Analyst Machine Learning Nanodegrees

Udacity is making two nanodegrees available for Udacity Connect or Udacity intensive: Data Analyst and Machine Learning Engineers. Its in-person meetup lessons utilizes the online material but features a bootcamp-like part-time learning opportunity with industry / professional classmates. Here are some PROs and CONs of Udacity Intensive Connect

  • PROs
    • Affordable price tag
      • The intensive class unlocks the corresponding online material for months, it is a much better deal than Udacity expensive monthly nanodegree price tag well north of $100
      • It's a bargain compared to coding bootcamps
    • Udacity markets its program as : bootcamp level intensity, in-person collaboration, accountability, part-time, no need to leave or quit your current job
    • Fast paced, stringent project timeline
    • Attend classes with diverse and experienced industry professionals
    • In-person lectures that are more targeted and easily adjusted for the needs of the class. High quality, in-person lectures, Q&A opportunities, one-on-one help. 
  • CONs
    • It is still expensive the price tag will be near $1000 or more
    • The physical location may be an hour away from your current location. I had to commute from San Francisco to San Jose. Ultimately it didn't work out. 
    • It still relies heavily on the online videos. If those videos didn't speak to you, the in-person interactions may not be able to shift your learning retention.  
    • Fast paced, stringent project timeline
    • Attend classes with diverse and experienced industry professionals. Not always beginner friendly
    • It is a significant time commitment
    • A lot of studying on the side, additional studying, looking up additional materials is required. The online videos will not provide all the information needed to complete the projects.
    • Significant in-person time commitment. Not attending the sessions will cause you to lose a lot of materials as they are not available online. It will put you behind schedule. I had to miss sessions because of business trips and it was hard to catch up.
Conclusion: for me personally, Udacity Connect or Udacity intensive helped me finish the Machine Learning Engineering Nanodegree. It has some rough spots as the program is in its early stages. But it is improving fast! Over the few months of learning, I could see the program changing. This program did get me start to think about Machine Learning in depth. I have discovered my interest. Once you know what machine learning is, it is easy to learn it online. A lot of time will be spent playing with datasets hands-on any way. Without those practices, it is not possible to take on a real job as a machine learning engineer. Your connect experience can vary with the instructor and classmates, as all inter-personal interactions do. 

The holy grail question: can you become a machine learning engineer after completing the nanodegree?
No, your knowledge, experience will not be sufficient. People get Phd's in this field. But it will open you up for some pretty awesome career paths.  More practice, knowledge acquisition is needed. You will need a strong portfolio of exemplifying projects. You will become a much better data analyst, putting you closer to a data scientist role than an analyst role. The Nanodegree will not be sufficient to get you a job at Google. However, if you are already experienced, already in the industry, just need some technical skills to climb over a hill, this course can really help you make the transition internally. 

Udacity Machine Learning Nanodegree Instructors Review


  • Georgia Tech Udacity online master degree instructors
    • This nanodegree utilizes video clips from the Georgia Tech Udacity computer science and engineering classes. The instructors are obviously highly qualified, technical and academic, but give sometimes nerdy and perhaps less engaging and relevant jokes and try to forcefully inject a sense of humor into the learning material. It didn't work out so well. Their explanation is professional and academic but less accessible to beginners. MINUS 
  • sebastian thrun and katie malone
    • Sebastian Thrun was a professor, successful entrepreneur, founder of Udacity, and the lead for many important Google businesses such as the self driving car. He's a really good teacher and gives valuable information on how machine learning is directly used in the industry. He is a god-like teacher in machine learning. PLUS!
    • Katie Malone was a student and a researcher and now a creator of several Udacity Machine Learning courses. She is great at explaining difficult concepts to beginners and advanced learners. She uses real life research examples, data sets from Kaggle, and simplifies the problems into workable problem sets for students. PLUS!
  • In-person lead Udacity Connect Intensive
    • If you join the Udacity Connect Intensive, you may get an in-person lead. He is usually a very qualified tutor and instructor. He/ she may not have the experience that Sebastian has, but is perhaps more practical and accessible for beginners. My session lead was once a Caltech lecturer, so he could go beginner friendly and also expert friendly. 
  • Conclusion: Udacity instructors are industry experts, academics, and highly experienced professionals in machine learning. However, despite each clip is high quality, the Udacity Machine Learning Nanodegree curriculum is patched together not in a cohesive manner. This curriculum will pose significant difficulty for people starting from scratch. Experienced professionals, professionals who had exposures to machine learning will have an easier time. 

Tuesday, January 3, 2017

Python crowned as the language of choice of data scientists

kaggle, a popular dataset data science machine learning competition site revealed in its recent Year In Review 2016 newsletter that Python has surpassed R as the language of choice for data scientists in recent years.this trend has been continuing for a few years. Kaggle's kernel language is now overwhelming Python despite that R was still popular and fresh in 2015. Why do you think that's the case? no revelation on Kaggle yet. Could it be because of increasing popularity of machine learning and specifically deep learning? Python works so well with ML

Monday, January 2, 2017

Codecademy Walkthrough SQL Table Transformation 01


Codecademy Walkthrough SQL Table Transformation 01
using SELECT * FROM tablename LIMIT 10;


How to be viral on Imgur and Reddit?

It is harder to be viral on Reddit and Imgur, one of the most popular image sharing, story telling site on the internet. It is not the best place to sell product, but it surely it is the best place to spread ideas and causes. It is also a great place to stay on top of current news and learn lifehacks. Like all forums, especially producthunt and hackernews, Imgur has its own algorithm to test out if a post should stay on its FrontPage, which essentially features the post and makes it viral. Below is a screenshot that has made it to the FrontPage, it also happens to explain how Imgur evaluates and weighs posts. Be aware, this is likely NOT the actual algorithm, but the actual model will look very similar to this. 


Rules of Sudoku for Algorithm Exercises

Need to code a Sudoku solver? Here are three rules of Sudoku: A 9x9 grids, Each row ... Each column ... Each of the 9 3x3 grids (examp...