People are optimistic about problem solving, but in most cases this is easier said than done. How do you do it?

In Adobe’s 2016 global study on creativity in business, 96% of people identified creativity as essential to their success, both in terms of their income and the value they bring to the world. Moreover, 78% wished they were capable of thinking differently, believing that they would progress through their careers more quickly if they did.

According to Malcom Gladwell, the world's most successful people have one thing in common: they think differently from most everyone else.  In his book, How Successful People Think, Malcom opens with the following:        “Good thinkers are always in demand.  A person who knows how may always have a job, but the person who knows why will always be his boss. Good thinkers solve problems, they never lack ideas that can build an organization, and they always have hope for a better future”
Too often we attribute creative and “different” thinking to natural, innate characteristics that belong only to the lucky. The truth is that you can study how ridiculously successful people think and incorporate their approach into your world.

Snippets and Quotes from Tech Innovators.
 

Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”

In this tutorial I am going to give you a gentle introduction to network programming in Python. If you are new to programming or new to Python then that may seem like a daunting thought. But read on and you will be pleasantly surprised how easy it is.

Like most modern programming languages, Python was designed for networking from the very beginning, and thanks to that, a lot of the networking tasks you would want to accomplish with the language are made a whole lot easier.

Network communication is a large topic, but if it is something that interests you then read on because in this tutorial I will show you how to download a web page. I will show you how easy Python makes tasks like this.

Take a look at the following code:

import urllib
	
con = urllib.urlopen("http://hartmannsoftware.com")
page = con.read()
con.close()
print page

As part of our C++ Tutorials series, here is a free overview of C++ pointers you may enjoy and find beneficial.

C++ Pointers Tutorials