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
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oreillyJust Enough Math
 
3.5

(based on 6 reviews)

Ratings Distribution

  • 5 Stars

     

    (3)

  • 4 Stars

     

    (1)

  • 3 Stars

     

    (0)

  • 2 Stars

     

    (0)

  • 1 Stars

     

    (2)

67%

of respondents would recommend this to a friend.

Pros

  • Helpful examples (4)
  • Easy to understand (3)

Cons

No Cons

Best Uses

No Best Uses
    • Reviewer Profile:
    • Developer (3), Educator (3)

Reviewed by 6 customers

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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.

    (3 of 6 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.

                (12 of 16 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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