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Every now and then, I keep seeing a new company coming up with Hadoop classes/courses. Also, my friends keep asking me which of these courses is good to take. I gave them a few tips to choose the best course suitable for them. Here are the few tips to decide which course you should attend to:
1. Does the instructor have domain expertise?
Know your instructor. You must know about the instructor’s background. Has (s)he done any big data related work? I have seen a lot of instructors who just attend a course somewhere and become instructors.
If the instructor never worked in the domain, do not take such classes. Also, avoid training institutes that do not tell you details about the instructor.
2. Is the instructor hands on? When did she/he code last time?
In the domain of technology, there is a humongous difference between one instructor who is hands-on in coding and another who is delivering based on theoretical knowledge. Also, know when the instructor worked on codes the last time. If instructor never coded, do not attend the class.
3. Does the instructor encourage & answer your questions?
There are many recorded free videos available across the internet. The only reason you would go for live classes would be to get your questions answered and doubts cleared immediately.
If the instructor does not encourage questions and answers, such classes are fairly useless.
Apache Flume is a distributed, reliable, and available system for efficiently collecting, aggregating & moving large data from many different sources to a centralized data store.
Flume supports a large variety of sources Including:
tail (like unix tail -f),
log4j – allowing Java applications to write logs to HDFS via flume
Flume nodes can be arranged in arbitrary topologies.Typically there is a node running on each source machine, with tiers of aggregating nodes that the data flows through on its way to HDFS.
What is Flume
Flume: Use Case
Flume: Use Case – Agents
Flume: Multiple Agents
Flume: Delivery Reliability
Introduction to Flume Presentation
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If you wish to learn Hadoop and Spark technologies such as MapReduce, Hive, HBase, Sqoop, Flume, Oozie, Spark RDD, Spark Streaming, Kafka, Data frames, SparkSQL, SparkR, MLlib, GraphX and build a career in BigData and Spark domain then check out our signature course on Big Data with Apache Spark and Hadoop which comes with
Online instructor-led training by professionals having years of experience in building world-class BigData products
High-quality learning content including videos and quizzes
Automated hands-on assessments
90 days of lab access so that you can learn by doing
24×7 support and forum access to answer all your queries throughout your learning journey
Confused whether to take up a career in Big Data or not? Planning to invest your time in getting certified and to acquire expertise in related frameworks like Hadoop, Spark etc. and worried whether you are making a huge mistake? Just spend a few minutes reading this blog and you will get six reasons on why you are making a smart choice by selecting a career in big data.
Why Big Data?
There are several people out there who believe that Big Data is the next big thing which would help companies to spring up above others and help them position themselves as the best in class in their respective sectors.
Companies these days generate a gigantic amount of information irrespective of which industry they belong to and there is a need to store these data which are being generated so that they can be processed and not miss out on important information which could lead to a new breakthrough in their respective sector. Atul Butte, of Stanford School of Medicine, has stressed the importance of data by saying “Hiding within those mounds of data is the knowledge that could change the life of a patient, or change the world”. And this is where Big Data analytics play a very crucial role.
With the use of Big Data platforms, a gigantic amount of data can be brought together and be processed to develop patterns which would help the company in making better decisions which would help them to grow, increase their productivity and to help create value to their products and services.
Our past two Bootcamp on Machine Learning at National Singapore University and RV College of Engineering were very interesting and all the attendees found it very useful. These feedbacks prompted us to have more Bootcamps like these.
Thanks to Prof. Alankar, who invited us to conduct yet another Machine Learning Bootcamp at Indian Institute of Technology, Bombay. Before we move on to the details of Bootcamp, let us give you a brief introduction to Prof. Alankar. He is an Assistant Professor at IIT Bombay in Mechanical Engineering Department and works in the area of Multiscale Modeling of Deformation. He is a graduate of IIT Roorkee, holds a masters degree from University of British Columbia (Canada) and doctoral degree from Washington State University (USA). He has previously worked at Max-Planck Institute (Germany), Los Alamos National Laboratory (USA) and Modumetal, Inc (USA).
Machine Learning Bootcamp
So it all happened on Mar 17 where Machine Learning enthusiasts, which includes professors and students from every branch of IIT, gathered to attend the one day workshop on Machine Learning. The presenter was none other than Mr. Sandeep Giri, who has over 15 years of experience in the domain of Machine learning and Big Data technologies. He has worked in companies like Amazon, InMobi, and D. E. Shaw.
In this post, we will show you how you can install Hortonworks Data Platform on AWS.
You can also watch the video of this tutorial here
We start with three machines. We could install Hadoop on these machines by manually downloading and configuring them, but that’s very insufficient. So either we could use Cloudera manager or Ambari. In this tutorial, we are going to use Ambari. On the first machine, we are going to install the Ambari server. For that, we need to buy these three instances at Amazon and we will follow the Ambari guidelines.
Ambari will then install all the components that are required in other two machines.
Please note, we will use 16 GB ram machines so that installation goes smoothly.
Cloudxlab has conducted many successful online events on Machine Learning and Big Data, for it is relatively easy to attend so many attendees simultaneously. Furthermore, it eliminates the need for a tiring visit to the event location. One can simply log in from the comfort of one’s house and start learning.
Sure, online events have their own perks. But it hasn’t stopped us to conduct offline events. Our Machine Learning session at R.V College of engineering was one such successful example.
This time, we wanted to conduct a little bigger event, therefore Cloudxlab joined hands together with IOTSG and National Singapore university, enterprise to organize another successful Machine Learning Bootcamp.
CloudxLab was organizing the Machine learning Bootcamp for the first time in Singapore. To be frank, we were a little nervous as we did not know how welcoming the country is. But all our minor doubts were cleared once we experienced the warm welcome from everyone there. So much so that we would like to do one more Bootcamp in Singapore in near future.
National Singapore University was very cooperative in helping us to organize the Bootcamp in their campus.
Have you ever wondered how you can apply various Machine Learning and IOT techniques for everyday business problems? Or, are you someone who has heard of Machine Learning but couldn’t get a chance to dig a little deeper? If your answer is Yes, then you’ve come to the right place.
Cloudxlab is conducting a Machine Learning & IoT Bootcamp in Singapore.
An exposure to Machine Learning using Python to analyze, draw intelligence and build powerful models using real-world datasets. You’ll also gain the insights to apply data processing and Machine Learning techniques in real time.
After completing this workshop, you will be able to build and optimize your own automated classifier to extract insights from real-world data sets.