Job : Python Developer in Hyderabad
Valuelabs company is looking for a Python Developer in Hyderabad location. The following are the details :
Company: Valuelabs
Position: Python Developer
Qualifications: Any Bachelor’s degree
Experience: 4-7 years
Skillset:
- Implement, deploy and maintain complex software solutions that fully satisfy the business requirement.
- Good understanding of the software development life cycle.
- Should be able to understand the requirements and implement independently
- Strong analytical skills, excellent problem solver and self-starter.
- Able to articulate and summarize complex solutions through technical discussions.
- Effectively communicate (written, verbal) issues and solutions in a clear, consistent manner through appropriate methods (voice calls, email, instant messaging, and ticketing systems).
Apply: Apply Here
Job : Java Developer in Hyderabad
Capgemini company is looking for a Java Developer in Hyderabad location. The following are the details :
Company: Capgemini
Position: Java Developer
Qualifications: Any Bachelor’s degree
Experience: 4-9 years
Skillset:
- Strong Core Java and spring.
- Strong experience on Microservices and SpringBoot
- Strong RESTFUL web service experience
- Strong SQL (preferably Oracle), JQuery, HTML/CSS, Oracle Restful, SOAP web services
Apply: Apply Here
Job : Network Engineer in Hyderabad
AMD company is looking for a Network Engineer in Hyderabad location. The following are the details :
Company: AMD
Position: Network Engineer
Qualifications: Any Bachelor’s degree
Experience: 0-2 years of Enterprise / Telecom Network infrastructure relevant experience
Skillset:
- Remote Network monitoring and ticket queue management
- Knowledge on network monitoring for Large Data Centers, Large WAN/Network environment
- Up-to-date knowledge and understanding of your employer's business and industry needs, as well as the technical demands
- Knowledge/experience on network device administration (Cisco, Juniper, F5 BigIP, Riverbed, Wireless, Fiber optic skills, MPLS/WAN/LAN management)
- Knowledge/experience with inter-network routing architectures, and the underlying network security technologies
- Recognize the importance of customer focus and/or of serving the needs of the end user
- Productivity Tools: Word, Excel, PowerPoint & Visio.
Apply: Apply Here
Common Words used in Computer Science Engineering
- Algorithms: An abstract computational procedure which takes values or some value and produces a value or values as output
- A Program is an expression of an algorithm
- Problem: Specification of what are valid inputs and what are acceptable outputs for each valid input
- Input instance: A value x is an input instance for problem P if x is a valid input as per the specification.
- Output: The information we get from the computer
- Bug: An error in the code that's causing the program to not run as expected
- Debug: Ways to find out the bugs in the code
- Testing: Check the program is working correctly for all the possible inputs
- Editor: A place to write the code
- Testcase: Inputs given to the program to test its functionality
Introduction to Machine Learning
This post helps you understand the very basic of Machine Learning.
The Machine Learning is divided into two categories :
The Machine Learning is divided into two categories :
- Supervised Machine Learning
- Unsupervised Machine Learning
There is also a category called Semi-Supervised Machine Learning.
Before going into the categories, let us explore what is the Machine learning.
So far, we have used many software applications in our day to day life. But with time, the data stored in these applications has increased enormously. Now a days from schools to hospitals, every one is using a computer to store the details of their respective customers. In case of schools, every year 100's of students join as well as graduate, all their details are saved in a database. The data in this database has increased exponentially with time. This huge amount of data is the key asset for Machine Learning.
Machine Learning is an art of making the machines intelligent with out programming explicitly. What it means is that you need not handle all the possible scenarios when you are writing the code, the machine has to predict the output. For the purpose of predict the outcomes, there are many algorithms/techniques designed for Machine Learning.
The key elements in any machine leaning algorithms are as follows :
- Process the data
- Identify which type of problem it is like regression, classification etc.
- Create a model
- Test and Improve the model with the experience
By following the above elements you will be able to build the algorithms for Machine Learning.
Understand Linked List
To have a clear picture of how a linked list is working, Let's take the example of Houses. First, think of these questions.
- Does every house on the earth has a unique identifying location?
- How do you visit your friend's house?
- Do you visit with the help of the address?
So the address here is similar to the reference of the object. Apart from storing the data, we also store the reference to the next object. In this way, links are created between the objects so when you want to move to the next object you will use the reference and get the data of the next object.
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