Learn to Use Git in 10 Minutes

If you’ve never used Git for your projects before, essentially, it tracks text changes, but its actual definition is a version control system. It’s the go-to standard for code versioning because of its distributed nature, as opposed to centralized Apache Subversion (SVN).

Git is the most commonly used version control system. Git tracks the changes you make to files, so you have a record of what has been done, and you can revert to specific versions should you ever need to. Git also makes collaboration easier, allowing changes by multiple people to all be merged into one source.

Installing Git

To check if you have Git installed in your system, run in your terminal:

git version
## git version 2.30.1 (Apple Git-130)

If you don’t have it yet, follow the instructions on :

https://git scm.com/downloads.

Mac users can install it with brew: brew install git 

#github #git

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Best Practices for Using Git

Git has become ubiquitous as the preferred version control system (VCS) used by developers. Using Git adds immense value especially for engineering teams where several developers work together since it becomes critical to have a system of integrating everyone’s code reliably.

But with every powerful tool, especially one that involves collaboration with others, it is better to establish conventions to follow lest we shoot ourselves in the foot.

At DeepSource, we’ve put together some guiding principles for our own team that make working with a VCS like Git easier. Here are 5 simple rules you can follow:

1. Make Clean, Single-Purpose Commits

Oftentimes programmers working on something get sidetracked into doing too many things when working on one particular thing — like when you are trying to fix one particular bug and you spot another one, and you can’t resist the urge to fix that as well. And another one. Soon, it snowballs and you end up with so many changes all going together in one commit.

This is problematic, and it is better to keep commits as small and focused as possible for many reasons, including:

• It makes it easier for other people in the team to look at your change, making code reviews more efficient.
• If the commit has to be rolled back completely, it’s far easier to do so.
• It’s straightforward to track these changes with your ticketing system.

Additionally, it helps you mentally parse changes you’ve made using git log.

#open source #git #git basics #git tools #git best practices #git tutorials #git commit

What is Machine learning and Why is it Important?

Machine learning is quite an exciting field to study and rightly so. It is all around us in this modern world. From Facebook’s feed to Google Maps for navigation, machine learning finds its application in almost every aspect of our lives.

It is quite frightening and interesting to think of how our lives would have been without the use of machine learning. That is why it becomes quite important to understand what is machine learning, its applications and importance.

To help you understand this topic I will give answers to some relevant questions about machine learning.

But before we answer these questions, it is important to first know about the history of machine learning.

A Brief History of Machine Learning

You might think that machine learning is a relatively new topic, but no, the concept of machine learning came into the picture in 1950, when Alan Turing (Yes, the one from Imitation Game) published a paper answering the question “Can machines think?”.

In 1957, Frank Rosenblatt designed the first neural network for computers, which is now commonly called the Perceptron Model.

In 1959, Bernard Widrow and Marcian Hoff created two neural network models called Adeline, that could detect binary patterns and Madeline, that could eliminate echo on phone lines.

In 1967, the Nearest Neighbor Algorithm was written that allowed computers to use very basic pattern recognition.

Gerald DeJonge in 1981 introduced the concept of explanation-based learning, in which a computer analyses data and creates a general rule to discard unimportant information.

During the 1990s, work on machine learning shifted from a knowledge-driven approach to a more data-driven approach. During this period, scientists began creating programs for computers to analyse large amounts of data and draw conclusions or “learn” from the results. Which finally overtime after several developments formulated into the modern age of machine learning.

Now that we know about the origin and history of ml, let us start by answering a simple question - What is Machine Learning?

#machine-learning #machine-learning-uses #what-is-ml #supervised-learning #unsupervised-learning #reinforcement-learning #artificial-intelligence #ai

Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

• revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
• microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
• Anaconda 4.2 – Anaconda is an opensource Python package

#machine learning #sql server #executing python in sql server #machine learning using python #machine learning with sql server #ml in sql server using python #python in sql server ml #python packages #python packages for machine learning services #sql server machine learning services

7 Best Practices in GIT for Your Code Quality

There is no doubt that Git plays a significant role in software development. It allows developers to work on the same code base at the same time. Still, developers struggle for code quality. Why? They fail to follow git best practices. In this post, I will explain seven core best practices of Git and a Bonus Section.

1. Atomic Commit

Committing something to Git means that you have changed your code and want to save these changes as a new trusted version.

Version control systems will not limit you in how you commit your code.

• You can commit 1000 changes in one single commit.
• Commit all the dll and other dependencies
• Or you can check in broken code to your repository.

But is it good? Not quite.

Because you are compromising code quality, and it will take more time to review code. So overall, team productivity will be reduced. The best practice is to make an atomic commit.

When you do an atomic commit, you’re committing only one change. It might be across multiple files, but it’s one single change.

2. Clarity About What You Can (& Can’t) Commit

Many developers make some changes, then commit, then push. And I have seen many repositories with unwanted files like dll, pdf, etc.

You can ask two questions to yourself, before check-in your code into the repository

1. Are you suppose to check-in all these files?
2. Are they part of your source code?

You can simply use the .gitignore file to avoid unwanted files in the repository. If you are working on more then one repo, it’s easy to use a global .gitignore file (without adding or pushing). And .gitignore file adds clarity and helps you to keep your code clean. What you can commit, and it will automatically ignore the unwanted files like autogenerated files like .dll and .class, etc.

#git basics #git command #git ignore #git best practices #git tutorial for beginners #git tutorials

Git Commands You Can Use To Dig Through Your Git History

In this short article, we’ll be exploring some quick  git commands that can help us in digging through our repositories’ history of commits. We’ll look at

1. git log
2. git shortlog
3. git show
4. git rev-list

#git #git-log #git-commands #git-history #aws