It’s that time of year again when I look into the Crystal Skull…er, ball, and make some predictions of the continuing challenges and new trends I foresee in Big Data and Data Science for the coming year.
Digital Transformation moves beyond just…Continue
Added by Bill Schmarzo on December 5, 2018 at 8:43am — No Comments
On 3 Dec 2018 when the US treasury yield curves inverted (a short-term US government bond yield is higher than its long-term yield), Economists quickly warned the stock market of an impending economic slowdown or even a recession. The following…Continue
Added by Zhongmin Luo on December 5, 2018 at 1:00am — No Comments
By Gunnar Carlsson
December 3, 2018
Added by Jonathan Symonds on December 4, 2018 at 3:00pm — No Comments
Summary: Sales is supposed to be an area that is more immune to replacement by AI than many others because of the high level of impromptu and improvisational human contact required. That remains true. But AI is showing that it can be a valuable augment to B2B sales and some early adopters are scoring big gains.
Added by William Vorhies on December 4, 2018 at 9:59am — No Comments
When it comes to Data Science, the most recurring topic is modeling. Quite a few articles out there talk about data preparation and only a bunch about how to communicate your results properly. However, there are hardly any dealing with the topic that we are going to cover today: data enrichment.Continue
Added by Juraj Kapasny on December 3, 2018 at 1:30am — No Comments
Data science is an interdisciplinary field of scientific processes, methods, and systems. It is used to extract insights from data in many forms, either structured or unstructured. With data at its core, it employs an extensive range of methods on the data to extract crucial insights from it.
This was a brief Introduction to Data Science. If you choose to set out on Python for Data Science, we’ve compiled a to-do list for you:
Learn Python for Data Science – The…Continue
Added by Richa Ojha on December 3, 2018 at 1:00am — No Comments
Do the usual (attending data camps if you don't have any experience), and you will go nowhere due to competition doing the exact same thing as you. Do the unusual, you will go nowhere either in terms of landing a job, as nobody understands what you do. However, the big difference is that in the latter case, you can compete with employers who won't hire you, and you can eat their lunch. That is what Uber, AirBnB, PayPal, Google, Zillow (predicting home values) and many more did, all of them…Continue
Added by Vincent Granville on December 2, 2018 at 10:30am — No Comments
I'm reposting this blog (with updated graphics) because I still get many questions about the difference between Business Intelligence and Data Science. Hope this blog helps.
I recently had a client ask me to explain to his management team the difference between a Business Intelligence (BI) Analyst and a Data Scientist. I frequently hear this question, and typically resort to showing Figure 1 (BI Analyst vs. Data Scientist Characteristics chart, which shows the different attitudinal…Continue
Added by Bill Schmarzo on December 2, 2018 at 7:00am — No Comments
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, outliers, regression, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting, dataviz, AI and many more. To keep receiving these articles, …Continue