Just Enough Math
Advanced Math for Business People to Leverage Big Data
By Paco Nathan
Publisher: O'Reilly Media
Final Release Date: May 2014
Run time: 5 hours 42 minutes

With the commercial successes of machine learning and cloud computing, many business people need just enough math to take advantage of open source frameworks for big data. This video course from Paco Nathan and Allen Day presents useful areas of advanced math in easy-to-digest morsels. If you’re familiar with high school Algebra 2 and basic statistics, you’re good to go.

You’ll learn newly introduced math concepts through business use cases, brief Python code examples, and lots of figures and illustrations. By the end of the course, you’ll understand how to leverage complex graphs, sparse matrices, Bayesian priors, optimization solvers, and other tools.

  • Learn advanced math through simple equations and illustrations
  • Get tangible examples such as Lego blocks for data workflows
  • Explore the math examples through typical business use cases
  • Understand how these concepts tie into common business frameworks
  • Follow a case study of the Foobartendr.io company throughout the course
Table of Contents
Product Details
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Customer Reviews

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oreillyJust Enough Math
 
3.6

(based on 8 reviews)

Ratings Distribution

  • 5 Stars

     

    (4)

  • 4 Stars

     

    (1)

  • 3 Stars

     

    (1)

  • 2 Stars

     

    (0)

  • 1 Stars

     

    (2)

71%

of respondents would recommend this to a friend.

Pros

  • Helpful examples (5)
  • Easy to understand (4)
  • Accurate (3)
  • Concise (3)
  • Well-written (3)

Cons

No Cons

Best Uses

  • Novice (3)
    • Reviewer Profile:
    • Developer (4), Educator (3)

Reviewed by 8 customers

Displaying reviews 1-8

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(1 of 1 customers found this review helpful)

 
3.0

Not a "Great Bang for your Buck"

By HF##

from Melbourne, Australia

About Me Developer, Working on a PHD in Machine Learning

Verified Reviewer

Pros

  • Lots of references

Cons

  • Very High Level

Best Uses

  • Expert

Comments about oreilly Just Enough Math:

What's good about this video :
=======================
1. It shows that Paco is a very knowledgeable and an experienced Data Scientist.
2. It offers many references to useful books and websites.
3. It provides a very high level overview of Data Science and the role of Modern Maths in it.
4. It uses a few Python examples to illustrate certain topics.

************************************

In my opinion the video does not deliver on its promises:
===========================================
1. "This video course from Paco Nathan and Allen Day presents useful areas of advanced math in easy-to-digest morsels." - for me this was not true - I failed to digest "some" of the material!

2. "If you're familiar with high school Algebra 2 and basic statistics, you're good to go." - even though I am familiar with high school Algebra 2 and basic statistics I don't feel "am good to go" after watching this video - in fact, now, I am more confused about Maths for Machine Learning after watching the video than before watching it.

3. "By the end of the course, you'll understand how to leverage complex graphs, sparse matrices, Bayesian priors, optimization solvers, and other tools." - not really!! I wish this was true. That was the main reason why I purchased this Video.

*******************

I've given this Video 3 stars.
I think that Paco deserves 5+ stars, he knows his stuff very well, he gave us a lot of references, he tried to cramp as much math concepts for ML in this short course as possible, which is probably where things went wrong for me. I wouldn't mind buying 10 such videos as a series of videos, where each video targets and really focuses deeply on one/two aspect(s) of ML and Math, with hands-on exercises.

P.S> Would have been good if the slides were also available for download - trying to type web links into the browser and distinguishing between lower-case "L" and "1" was a real pain! Also wish the Py examples were real Py files instead of Py-in-HTML pages

 
5.0

very helpful overview

By Jesse

from Plano, TX

About Me Maker

Pros

  • Accurate
  • Concise
  • Easy to understand
  • Helpful examples
  • Well-written

Cons

    Best Uses

    • Intermediate
    • Novice

    Comments about oreilly Just Enough Math:

    This course provided me with a helpful survey of how advanced math concepts are being adopted in the field of data science.

    I especially appreciated the additional context highlighting key developments of the concepts and debates in the field.

    (1 of 1 customers found this review helpful)

     
    5.0

    Great Bang for your Buck

    By mdwaldman

    from Boulder, CO

    About Me Designer, Developer, Sys Admin

    Pros

    • Accurate
    • Concise
    • Helpful examples

    Cons

      Best Uses

      • Intermediate

      Comments about oreilly Just Enough Math:

      Great overview, yet in-depth analysis of the ingredients needed for successful data science implementation.

      Presentation of the mathematics was intuitive, yet comprehensive enough to guide the reader's understanding of the skills needed for the emerging field of data science.

      (4 of 11 customers found this review helpful)

       
      1.0

      Very disappointing

      By Disappointed

      from San John

      About Me Developer

      Pros

        Cons

        • Irrelevant
        • Misleading

        Best Uses

          Comments about oreilly Just Enough Math:

          Extremely abstract and just plain confusing at times. Tons of irrelevant examples and links to books. First and last video with O'Reiley.

          (3 of 4 customers found this review helpful)

           
          5.0

          unique resource

          By dsiegel

          from Seattle, WA

          Verified Reviewer

          Pros

          • Easy to understand
          • Helpful examples
          • Well-written

          Cons

            Best Uses

            • Novice
            • Student

            Comments about oreilly Just Enough Math:

            The presenter's style has been an accessible keystone for motivating studies in the recommended materials. If you have an appetite for building parallelizable data products, and lack a grad degree in mathematics or computer science, this material will be a resource to form the basis for understanding a winning approach, including contexts to be considered when building high ROI apps. Integers and legos are presented as conceptual examples for code re-use, parallelization, and reduced latency.

            If you're not remotely comfortable with abstraction, and want just facts and details, you might disagree with my rating.

            One strength here is that you can follow business examples through several hypothetical applications, using the code repository. This video also offers some future forward thinking to keep you on edge.

            (2 of 3 customers found this review helpful)

             
            5.0

            The math track you should have gotten

            By Lynn Bender

            from US / EU

            About Me Developer, Educator

            Verified Reviewer

            Pros

            • Accurate
            • Concise
            • Easy to understand
            • Helpful examples
            • Well-written

            Cons

              Best Uses

                Comments about oreilly Just Enough Math:

                The traditional Calculus/DiffEQ sequence currently taught in college was great for post WW2 engineers, but much less useful for today's CS student/pro. If you're interested in Data Science or Machine Learning, this course is an incredible introduction/roadmap for what you really need to know.

                (3 of 5 customers found this review helpful)

                 
                4.0

                helpful intro, many links

                By sarag

                from Baltimore, MD

                About Me Educator

                Pros

                • Easy to understand
                • Helpful examples

                Cons

                  Best Uses

                  • Novice

                  Comments about oreilly Just Enough Math:

                  The video provides many other references to follow for further study. The histories helped me understand more about where some of the techniques came from.

                  (16 of 22 customers found this review helpful)

                   
                  1.0

                  I would ask for money back

                  By toastmaker

                  from Dublin, Ireland

                  About Me Educator, Researcher

                  Verified Reviewer

                  Pros

                    Cons

                    • Low Information Density
                    • Poor Explanation
                    • Shallow
                    • Too basic

                    Best Uses

                      Comments about oreilly Just Enough Math:

                      Not sure if it's my or author's fault but I find this video very close to garbage. Half of the video time is spent writing primitives on the white board, explanation of terms is very shallow, not coherent, often irrelevant, subjects from each section are not linked with each other while the most repetitive statement that matters is "you can learn this in the book X" (e.g. X=Think Bayes). It was my first O'Reilly's video lecture series based on the promising table of content however, I am quite disappointed.

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