Subrat's Technical Blog

This year, we’ve seen a 56% increase in data science jobs according to TechRepublic . Data science jobs such as data scientists, data engineers, data analysts, and machine learning engineers are booming. Increasingly, software engineers and developers are working side by side with these data professionals. It’s essential for anyone on a development team to understand some of the basics of data science, statistics, and machine learning. Picking up any of one of the below books will give you some knowledge and understanding of important areas of data science such as Statistics, Data Science, Machine Learning, and Deep Learning. Disclaimer: There are no affiliate links in this post. This post is for information purposes only. Math & Statistics Think Stats — by Allen B. Downey <img class="ds t u hm ak" src="https://miro.medium.com/max/652/1*LhBvXxJEbVOtUyB-sTN0Rg.png" width="326" height="380" role="presentation"/>

nowing that taking training at your own pace, when you have time, suits many people's schedules and learning style, Oracle has just releases new Training-on-Demand courses for those aspiring to build their Linux administration skills. Why not take advantage to the newly released training to build your Linux skills. Start your Linux learning with the  Oracle Linux System Administration I  course. This course covers a range of skills including installation, using the Unbreakable Enterprise Kernel, configuring Linux services, preparing the system for the Oracle Database, monitoring and troubleshooting. After gaining essential knowledge and skills from taking the  Oracle Linux System Administration I  course, students are encouraged to continue their Linux learning with  Oracle Linux System Administration II . The  Oracle Linux System Administration II  course teaches you how to automate the installation of the operating system and implement advanced software package ma

What if you want to host multiple Oracle JET applications? You can do it easily on Oracle Always Free Cloud. The solution is described in the below diagram: You should wrap Oracle JET application into Node.js and deploy it to Oracle Compute Instance through Docker container. This is described in my previous post -  Running Oracle JET in Oracle Cloud Free Tier . Make sure to create Docker container with a port different than 80. To host multiple Oracle JET apps, you will need to create multiple containers, each assigned with a unique port. For example, I'm using port 5000: docker run -p 5000:3000 -d --name appname dockeruser/dockerimage This will map standard Node port 3000 to port 5000, accessible internally within Oracle Compute Instance. We can direct external traffic from port 80 to port 5000 (or any other port, mapped with Docker container) through Nginx. Install Nginx: yum install nginx Go to Nginx folder: cd etc/nginx Edit configuration file: nano nginx.conf Add context

Oracle Cloud  Free Tier  was announced a couple of months ago at Oracle OpenWorld 2019. It was mentioned in one of my posts at the time ( here ). So what do you get for your zero dollars? 2 Autonomous Databases : Autonomous Transaction Processing (ATP) and/or Autonomous Data Warehouse (ADW). Each have 1 OCPU and 20G user data storage. 2 virtual machines with 1/8 OCPU and 1 GB memory each. Storage : 2 Block Volumes, 100 GB total. 10 GB Object Storage. 10 GB Archive Storage. Load Balancer : 1 instance, 10 Mbps bandwidth. Some other stuff… I’ve been using Oracle Cloud for a few years now. Looking back at my articles, the first was written over 4 years ago. Since then I’ve written more as new stuff has come out, including the release of OCI, and the Autonomous Database (ADW and ATP) services. As a result of my history, it was a little hard to get exited about the free tier. Don’t get me wrong, I think it’s a great idea. Part of the battle with any service is to get people using

The opportunity to leverage insight from data has never been greater. However, at this point, we do not have enough skilled employees to help us make sense of it all. So, if you want to be a data scientist, working with data in the next 10–15 years, then this is your time. Go win all those jobs! This blog would briefly focus on the concepts that you must know about before you appear for a Data Science entry-level interview. Through the length of the blog, I will cover a list of topics that help for an entry-level data Science interview, the amount of domain knowledge you need to have about it and BONUS: questions around a topic from my interviews!!! Traditionally, Data Science focuses on programming, mathematics, computer science and Machine Learning domain knowledge and we would take exactly on that! With tons of opportunities lying around for a data scientist, here’s my guide for a beginner Data Scientist. 1. Programming Languages Python and R are the most popular ones