DEV Community: Mohithsharma

Java Developer Resume

Mohithsharma — Mon, 14 Jun 2021 10:49:57 +0000

A Java developer is a specialist programmer who uses their knowledge to test and develop software using the Java programming language. Java developers use their knowledge to create, adapt, monitor and repair software across a variety of platforms, and Java developers often work closely with web developers and designers and software engineers to create fully integrated programs and applications for their clients.

You’re a Java developer. You’re smart. You develop complexities. But when it comes to writing a resume that shows off your talents, you’re lost.

Creating a resume isn’t the easiest of tasks, especially for a job as specific as Java developer.

Resume basically outlines your skills and training, work experiences, and educational background, and, most importantly, the accomplishments you have made with past employers. It also informs the hiring committee of your career objective and communicates concisely the benefits you will bring to the job if hired.

Some common resume ethic one should maintain is as follows:

Margins – One-inch margins on all sides
Font – Pick a professional font that stands out.
Font Size – Use a font size of 11-12pt for normal text and 14-16pt for headers
Line Spacing – Use 1.0 or 1.15 line spacing
Resume Length – Don’t go over the 1-page limit.

What Not To Do In Your Resume

On the contrary, one must keep in mind of what NOT to do in your resume, which follows:

Too much information
Spelling mistakes and grammatical errors
Inaccuracies about your qualifications or experience
Unnecessary personal information
Your age
Negative comments about a former employer
Details about your hobbies and interests
Passive language
Tiny text
Miscellaneous extra content

Launch Modes In Android

Mohithsharma — Fri, 04 Jun 2021 06:18:30 +0000

Android is a mobile operating system based on a modified version of the Linux kernel and other open source software, designed primarily for touchscreen mobile devices such as smartphones and tablets. Android is developed by a consortium of developers known as the Open Handset Alliance and commercially sponsored by Google. It was unveiled in November 2007, with the first commercial Android device, the HTC Dream, being launched in September 2008.

It is free and open-source software; its source code is known as Android Open Source Project (AOSP), which is primarily licensed under the Apache License. However most Android devices ship with additional proprietary software pre-installed, most notably Google Mobile Services (GMS) which includes core apps such as Google Chrome, the digital distribution platform Google Play and associated Google Play Services development platform.

About 70 percent of Android smartphones run Google's ecosystem; competing Android ecosystems and forks include Fire OS (developed by Amazon) or LineageOS. However the "Android" name and logo are trademarks of Google which impose standards to restrict "uncertified" devices outside their ecosystem to use Android branding.

Launch Mode

The different launch modes in Android are given below:

Standard:

This launch mode generates an activity’s new instance in the task from which it originated.
It is possible to create several instances for the same activity.
For Example, suppose our current stack is A -> B -> C. Now, if we launch activity B again with the “standard” launch mode, then the new stack will be A -> B -> C -> B.

SingleTop:

This launch mode is similar to the Standard launch mode except if there exists an activity’s previous instance on the top of the stack, then a new instance will not be created.
But the intent will be sent to the activity’s existing instance.
For example, suppose our current stack is A -> B -> C. Now, if we launch the activity B again with “singleTop” launch mode,then the new stack will be A -> B -> C -> B.
Consider another example, where the current stack is A -> B -> C. Now, if we launch activity C again with the “singleTop” launch mode, then the stack will remain the same i.e., A -> B -> C. The intent will be passed to the onNewIntent() method.

SingleTask:

This launch mode will create a new task and push a new instance to the task as the root.
For example, suppose our current stack is A -> B -> C -> D. Now, if we launch activity B again with the “singleTask” launch mode, then the new stack will be A -> B. Here, a callback has been received on the old instance and C and D activities are destroyed.

SingleInstance:

This launch mode is similar to the SingleTask launch mode. But the system doesn’t support launching any new activities in the same task.
In a situation where the new activity is launched, it is launched in a separate task.
For example, Suppose our current stack is A -> B -> C. Now, if we launch the activity D with the “singleInstance” launch mode, then there will be two stacks:
A -> B -> C
D, If you call activity E, then it will be added to the first stack.
A -> B -> C -> E
D

Again if you Call the activity D, then it will call the same activity from the 2nd stack and pass the intent to onNewIntent().
Content - InterviewBit

Supervised Vs Unsupervised ML

Mohithsharma — Wed, 07 Apr 2021 13:49:43 +0000

Supervised learning

Supervised learning as the name suggests is the presence of a supervisor who acts as a mentor. In simple words, supervised learning is a way in which we teach or train the machine using data that is well labeled. A well-labeled data is one that has some portion of data that already has the correct answer.

The machine is then provided with a new set of data in a way that a supervised learning algorithm analyses the set of existing data and produces a correct outcome from labeled data.

For instance, suppose you are given a basket filled with different kinds of vegetables. Now the first step is to train the machine with all different vegetables one by one like this:

If the shape of the object is rounded and depressed at top having the color Red with some green attached then it will be labeled as – Tomato.
If the shape of the object is a long curving cylinder having the color Light-Green then it will be labeled as –Bottle Gourd.

After training the data, you are given a new separate vegetable say Bottle Gourd, and asked to identify it. Since the machine has already learned the things from previous data and hence used it accordingly. It will first classify the fruit with its shape and color and would confirm the fruit name as BOTTLE GOURD and put it in that same place. Thus the machine learns the things from the existing labeled data of vegetables and then applies the knowledge to the new data entering the system.

Supervised learning can be of two types: Classification and Regression. A classification problem is the one when the output variable is a category, such as “Orange” and “Yellow” or “Vaccine” and “No Vaccine”. Meanwhile, a Regression Problem is the one when the output variable is a real value such as “Rupee” or “Lbs”.

The other types of Supervised Learning are Logistic Regression, K-NN, Decision Tree, and Support Vector Machine.

Supervised and Undervised ML is considered to be one of the frequently asked Machine Learning Interview Questions.

Advantages

Using previous experience output can be generated for the new data that is being collected
With the help of sequential learning by gaining experience the performance can be optimized.
Some real-life problems and challenges can be easily solved using this approach of supervised learning.

Disadvantages

The segregation of big data can be challenging and might lead to error.
Teaching the system for supervised learning is a time taking process.

Unsupervised Learning

Unsupervised learning is the training of machines using data points that do not have classified or labeled data. It allows the algorithm to act on its own without giving any specific direction. The machine is expected to group unorganized and unsorted data based on certain common traits, similarities, patterns, and differences without providing any teaching on the data set. It allows the machine to design the use case on its own and thus find hidden connections between data on its own.

For instance, an image of a tiger and a lion is given to the machine. The machine has no idea what is a tiger or a lion. about the features, patterns, color, similarities, or differences of lion and tiger. Hence, it will not be able to categorize it in tiger and lion. But it can categorize them according to the features, patterns, color, similarities, or differences of lion and tiger. In this system we were not taught anything before i.e no data was shown or given to us at the beginning of the process.

It allows the technique to work on its own by discovering patterns and information that was not known to the system before. It mainly deals with unlabelled data.

Unsupervised learning can be of two types:

Clustering
Association

The clustering problem is the one where we check for inherent grouping of data such as grouping cardholders based on their spending.
Whereas Association is the one where we discover a set of rules. That describes large portions of the data and brings an X on Y dependency.

The other types of Unsupervised Learning are Agglomerative, Overlapping, and Probabilistic. There are some clustering types like K-map and others that help in the same.

Supervised Vs Unsupervised

Supervised	Unsupervised
It has labeled data with which new data is processed.	It has unlabelled data and groupings are made without prior knowledge.
Comparatively Simpler.	Comparatively Complex.
Highly Accurate.	Not Accurate.

Conclusion

Machine Learning has come a long way and advanced in such a manner that is always on the move. Supervised and Unsupervised Learning are two realms of this world that differ in their approaches and complexity making each other complete.

Frequently Asked AWS Interview Questions

Mohithsharma — Wed, 31 Mar 2021 11:22:53 +0000

AWS is a cloud computing service offered by Amazon. AWS lets you build, test, deploy and manage applications and services. All this is done via the data-centers and the hardware managed by Amazon. AWS provides you a combination of Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS) offerings.

You can use AWS to create Virtual Machines which can be armed with processing power, storage capacity, and analytics along with networking and device management. AWS offers you a pay-as-you-go model, which helps to avoid upfront costs and pay based on the usage monthly.

This set of AWS Interview Questions from InterviewBit would help you clear you interview easily.

1 - What is EC2?
2 - What is SnowBall?
3 - What do you understand by VPC?
4 - What are the Storage Classes available in Amazon S3?
5 - Explain what T2 instances are?
6 - How many Subnets can you have per VPC?
7 - Explain what S3 is?
8 - How does Amazon Route 53 provide high availability and low latency?
9 - What are the different types of Instances?
10 - How do you monitor Amazon VPC?