Supervised Learning Probabilistic Neural Networks

Scalable Semi-supervised Deep Learning
supervised learning in While I've always been sympathetic to the goals of deep learning researchers, in practice deep learning techniques have not played a significant role in my career thus far. I've chosen to work for internet companies that have large amounts of data (behavioural data exhaust) in mostly discrete or textual form (e.g., text search ads, dating profiles, and tweets). Thus I have relied exclusively on shallow learning algorithms (linear or mildly nonlinear) and hand-tuned feature construction.
If deep learning were great, there would be no need to pay people like myself to massage the raw data into a form that is more amenable to shallow learning algorithms. I also don't think history will judge the ability of human feature engineering kindly. Textual data is an exception because it's easy to work with: naive encodings (e.g., bag of bigrams) are a great starting point, and there are many sources of side-information available that can be joined up against tokens. The computer vision community, in contrast, seems to face a much harder problem. Although historically their labeled data sets were small by internet standards, this has been mitigated in recent years due to crowdsourcing and public database definition efforts. So the problem seems to be that pixels are a harder

Source: Machined Learnings

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Recruiter Resume

2000-10-09 00:00:00 by Anon

Hello, I am a senior technical recruiter with both on-site and agency experience currently completing a contract. My experience includes recruiting for diverse senior technical and marketing/sales positions in both start-ups and established companies from Director level on down. I have sourced and placed both full-time and contract professionals in technical and technical marketing areas. I have placements in many well known companies including: HP, Evolve, Telephia, Platinum, Brooktree, EQE International, LifeScan (Johnson & Johnson), Retix, Mediashare, 3COM, IBM, Adobe, Network Associates, Match.com, Bank of America, Applied Materials, Sterling Software, Incyte, etc. Thank you for taking the time to review my resume. JACKIE JUGE Orinda, (East Bay) CA 94563 925-258-0651 jjuge@home.com...

But then there's Mike....

2006-03-02 08:22:27 by MasterPo

I again agree with you 110%.
But then there was Mike.
Mike was a guy I worked with some years ago at a small financial software company in mid-town NYC. He started as a software trainer. With in 6 months he was made manager of training (the current manager was demoted!). By the end of the year he was made a project manager. The next year he was made a systems analyst. And by the end of that year the leader of the analysis group was fired and he was installed as the new systems analysis team leader.
At lunch one day I asked him about his background. Afterall, must be something super to have made such an incredible rise through the ranks so quickly. Right? Not!!!!
By his own words his "career" (he was in his mid-30's) included jobs as a dog groomer, personal...

This job is total BS!

2002-07-22 15:22:11 by GladEyeLeftTheBayArea


Reply to: jobs@klfinancialgroup.com
Date: Mon Jul 22nd 12:18
SF-based hedge fund is seeking a summer intern to assist fund’s Director of Information in the development of a sophisticated information system performing technical analysis of the stock market and trading performance. Candidate should possess strong programming abilities, analytical skills, creative insight, and an undergraduate degree from a 4-year, accredited program in the area of MIS, Systems Analysis, Statistics, Finance or Accounting. Specifically, the candidate MUST have experience in the following: SQL Server 2000 (stored procedures), Visual Studio.NET (especially VB), MS Excel, and Windows 2000.
The 3-month internship is non-paying but will provide the candidate with great experience in the...

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