How to Setting up Environment Variables in MacOS Sierra ?

Step 1

Open the Terminal and Write the Command

printenv

Geek@Nasrullahs-MacBook-Pro bin $ printenv

Step 2

Set the required path

Export PATH ={NEW PATH}:$PATH

export PATH=/Users/Geek/Anaconda-2/anaconda2/bin:$PATH

How to set username in Git ?

Open Terminal

Set Git User Name Globally

$ git config --global user.name "Nasr Ullah"

$ git config --global user.name
> Nasr Ullah

Set Git User Name for a Single Repository

$ git config user.name "Nasr Ullah"

$ git config user.name
> Nasr Ullah

How to associates the Editors with Git on Mac?

Using ATOM as Editor in Git

Step 1 - Download the ATOM 
Step 2 - Install the ATOM
Step 3-  Open Terminal & Use the following command 

$  git config --global core.editor "atom --wait"








Using Sublime as Editor in Git

Step 1 - Download the Sublime
Step 2 - Install the Sublime
Step 3-  Open Terminal & Use the following command 

$  git config --global core.editor "subl -n -w"

Using TextMate as Editor in Git

Step 1 - Download the TextMate
Step 2 - Install the TextMate
Step 3-  Open Terminal & Use the following command 

$  git config --global core.editor "mate -w"

Hot Technologies for Data Science

It is really confusing when you read about the Data Science and its technologies; If found very helpful information from Forbes Magazine and DataCentral Websites.

Gil Press posted a list of top 10 hot big data technologies in Forbes Magazine. The technologies being featured as hot were:

• Predictive analytics
• NoSQL databases
• Search and knowledge discovery
• Stream analytics
• In-memory data fabric
• Distributed file stores
• Data virtualization
• Data integration
• Data preparation (automation)
• Data quality

DataCentral website wrote the article on it and mentioned the hottest technologies as they know are the hot one:

• Adapting modern predictive algorithms to a distributed architecture
• AI (pattern recognition)
• Deep learning (the interection of AI and machine learning)
• Data science automation
• Leveraging data from sensors (IoT)
• Turning unstructured data into structured data, and data standardization
• Blending multiple predictive models together
• Intensive data and model simulation (Monte-Carlo or Bayesian methods), to study complex systems such as weather, using HPC (high performance computing)

What do you think are the hottest technologies now? Do you agree with Gill & Vincent Granville?

References:
https://www.forbes.com/sites/gilpress/2016/03/14/top-10-hot-big-data-technologies/#4f0b566565d7http://www.datasciencecentral.com/page/search?q=2016+predictions

How to Install Scikit-Learn on MacOS

Scikit-learn requires:

• Python (>= 2.7 or >= 3.3),
• NumPy (>= 1.8.2),
• SciPy (>= 0.13.3).

MAC OS Command

Scikit-learn and its dependencies are all available as wheel packages for OSX:

pip install -U numpy scipy scikit-learn

How to find your iPhone , iPad UDID ?

Finding your iPhone, iPod touch or iPad’s unique ID (UDID)

Every iPhone, iPod touch and iPad has a unique identifier number associated with it, known as a UDID (Unique Device ID). Your UDID is a 40-digit sequence of letters and numbers that looks like this: 0e83ff56a12a9cf0c7290cbb08ab6752181fb54b. It’s common for developers to ask for your UDID as they require it to give you beta copies of iOS apps.

Finding your UDID using iTunes

• Open iTunes (the Mac or PC app, not iTunes on your iPhone).
• Plug in your iPhone, iPod touch or iPad.
• Click its name under the devices list.
• Ensure you’re on the Summary tab.
• Click on the text that says Serial Number. It should change to say Identifier (UDID).
• Select Copy from the Edit menu.
• Your UDID is now in the clipboard, so you can paste it into an email or message.

What are the Possible Data Science Team Members?

Following are the Team members required to build a Data Science Team :

1. Data Scientist

2. Data Engineer

3. Big Data Engineer

4. Machine Learning Scientist

5. Business Analytics Specialist

6. Data Visualisation Developer

7.  Business Intelligence (BI) Engineer

8. BI Solutions Architect

9. BI Specialist

10. Analytics Manager

11. Machine Learning Engineer

12. Statistician

13. Mathematician

You can add more.. :)

What is Data Science?

• Skills of Extracting Knowledge from Data
• Using Knowledge to Predict UnKnown
• Improve Business Outcomes with the power of data. 
• Employ different techniques and theories from statistics, mathematics and computer science