From Novice To Expert: Roadmap to become an expert in Machine Learning

There is no denying that machine learning is the future. With the advent of Big Data, the machine learning boom has taken the tech industry by storm. However, machine learning is not very easy. You have to invest a lot of time to become an expert in machine learning. The best way to approach machine learning is by a step-by-step guide. It will help you deal with the subject slowly without getting too overwhelmed by it. Here are a few ways which can make you a machine learning expert:

  1. Understanding the basics

Before diving into machine learning, you need to know what you are getting into. Just knowing a few basics will not help – you have to be aware of the finer details in machine learning. Learn what analytics, Big Data, Artificial Intelligence, Data Science are and how they are related to one another. 

  1. Learning basic statistics

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When you research on the basics of machine learning, you will often come across many statistical applications. So, what should be your next step? Brush up your statistics. You don’t have to be an expert in statistics, but you need to learn a few topics in statistics. It will be essential in machine learning. A few topics you should work on are sampling, data structures, linear and multiple regression, logistic regression, probability, etc.

  1. Learning a programming language

While researching machine learning, you will learn about the different programming languages which support machine learning. When you learn these programming languages, you become familiar with many applications of machine learning like data preparation, data cleaning, quality analysis, data manipulation, and data visualization.

  1. Taking up an Exploratory Data Analysis project

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Exploratory Data Analysis means analyzing data sets and then explaining or showing that summary presented by that data set, mostly in a visual format. In this project, charts, diagrams, or other visual representations can be used to display the data. A few topics that need to be covered here are Single variable explorations, visualization, pair-wise, and multi-variable explorations.

  1. Creating unsupervised learning models

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Unsupervised learning model is a machine learning technique where you do not need to supervise the model. It will discover information on its own and work on it. For example, if you give the basic parameters of several countries like population, income distribution, demographics, etc., unsupervised learning models can help you find out which countries are most similar. It uses unsupervised machine learning algorithms. It can be grouped into two kinds of problems: Clustering and Association. Two Unsupervised learning algorithms are k-means for clustering problems or the Apriori algorithm for association rule learning problems.

  1. Creating supervised learning models

Supervised learning models are a kind of learning where you teach and train the machine to use labelled data to arrive at the right conclusion. After training the machine with the labelled data, you have to provide some training examples to see if it produces the right outcome. For example, if you provide the specific descriptions of an apple (Red, Rounded) and a banana (Yellow, long curving cylinder) to the machine, then it can separate the two fruits and put them in their respective categories. Logistic regression and Classification trees are a few topics you need to cover here.

  1. Understanding Big Data Technologies

The machine learning models being used today were there in the past too. However, we can make full use of them now because nowadays, we have access to large amounts of data. Big data systems stores and control the vast amounts of data that are used in machine learning. So, if you are making your way to be an expert in machine learning, you should research and understand Big Data Technologies.

  1. Exploring Deep Learning Models

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Top tech companies like Google and Apple are working with deep learning models to make Google Assistant and Siri better. Deep learning models help machines listen, write, read, and speak. Even vehicle tests are now conducted using deep learning models. Learn about topics like Artificial Neural Networks, Natural Language Processing, etc. Start by making your model differentiate between a fruit and a flower. That’s a great start and will set a pattern for future learning.

  1. Completing a data project

Finally, find a data project and work on it. You can search for a data project on the internet. Work on it and showcase your skills. There’s nothing for fulfilling and educative as the proper application of machine-learning.

Benefits of Machine Learning

Machine learning is one of the most innovative technologies which is being used by top companies like Amazon, Apple, and Google. Now, the question is: what are the benefits of Machine learning? Here are a few benefits of machine learning:

  • Identifying trends and patterns

Machine learning can review large sets of data and identify trends and patterns based on it. For example, Amazon can direct notifications to buyers based on their purchasing and browsing history of a user.

  • Constant Improvement 

Machine learning algorithms improve over time. With the increase of data input, machine learning will be more accurate and help in making better predictions.

  • No human intervention 

With machine learning, machine algorithms learn by themselves and improve themselves automatically. So, you don’t have to invest all your time in it.

  • Different kinds of data 

Machine Learning algorithms can handle multi-dimensional and multi-variety data easily and is thus, very efficient in handling large data sets.

  • Many Applications

The applications of machine learning are expanding. From being used software like Siri to even driverless vehicle testing, machine learning is becoming the future in many industries. It is also being included in healthcare industries. Machine learning applications are far and wide.

Job Prospects of Machine Learning

Machine Learning is one of the hottest careers in the market right now. Top tech firms like Amazon, Google, and Apple, are integrating machine learning with their software. According to Gartner, AI will be creating 2.3 million jobs in 2020. These jobs will require research and developing algorithms. Machine learning scientists will have to extract patterns from Big Data too. Some hot career positions are:

  • Machine Learning Engineer
  • Machine Learning Analyst
  • Data Sciences Lead
  • Machine Learning Scientist
  • NLP Data Scientist 

Machine learning is going to be difficult, but in the end, it will be a fulfilling ride. If you wish for expert guidance, you can take help from the Coding Ninjas machine learning course.

How to start your journey to become a blockchain developer?

If you have been up-to-date with recent trends in technology, we can bet that you must have heard the term blockchain more than once in your lifetime. It must have intrigued you, and you would have surely realized the promise that blockchain holds, in order to look up “how to become a blockchain developer” on Google.

It isn’t as hard as it seems!

What exactly is the blockchain, and why should one look to become a blockchain developer?

In very basic terms, a blockchain is a database with a few special properties. It is decentralized, public, and the data is stored in the form of blocks, connected together to form a chain. Hence the name, blockchain. Each single data block is an immutable record of data, not owned by any single entity, rather managed by a cluster of nodes on the network.

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It was first brought to light by Bitcoin, although the scope for programming or development on the Bitcoin blockchain was limited. Blockchain is the technology that is used to process and record transactions on cryptocurrencies. Blockchain development really took off with the introduction of Ethereum, presenting to the world the first programmable blockchain. Ever since, blockchain development has evolved into a hot concept, with its popularity through the roof.

Blockchain development isn’t too dissimilar to regular programming, as further sections will present. The opportunity for an individual to create apps on top of a blockchain is as exciting as it sounds! Let’s see how to get on with it.

How to set off on this journey

Blockchain development, like any other task, involves a few prerequisites. If you are an absolute beginner when it comes to this technology, you would be better off researching and reading up on how it works, some key terms involved, and the overall process.

Once you are up to speed, first-hand experience with cryptocurrency is also a must. Developers usually skip this part and move on to coding, but in order to stand out from the others, learning how coins work is essential. Use a simple basic online wallet, create an account on any exchange services, and diversify as you go. Learning how exchanges work and getting familiar with wallets should be your focus.

When you have the know-how of all the processes of a blockchain, you can begin to visualize all the different parts that are coded into a blockchain application. For instance, if you are looking to build a wallet, the different parts might include setting up features to view balances, account details, and much more. What is actually done in programming is to connect these features together and communicate with the underlying network, which is blockchain in this case.

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Then comes the exciting part- coding! Blockchain development works on languages already established, and a few that are up and coming, designed specifically for the blockchain. 

Top programming languages for blockchain development

  • C++. The oldest of them all, C++ still provides a great amount of functionality and features to assist blockchain development. Blockchain demands speed and security, and C++ with its superior memory control can help achieve those objectives. With multithreading, you can make sure that your blockchain application is able to handle multiple tasks at once. Being mature, C++ is constantly updated, with debuggers and analytical tools available to help you code better. All these advantages tie in beautifully to the fact that C++ is, and for a long time, will be a great choice for blockchain development. 

Learn C++ with Coding Ninjas here! (https://www.codingninjas.in/courses/onlline-c-plus-plus-course)

  • Solidity. Moving on to a language that caters particularly to the blockchain, Solidity was actually developed by Ethereum. It utilizes C++’s object oriented programming constructs, as well as JavaScript’s functions. The language itself is not very complicated, but having a grasp of other modern languages like Python makes it easier. It is the go-to language for developing smart contracts, or decentralized apps (dapps). For developers looking to add smart contract functionality to their ledgers, like Ethereum, Solidity is the way to go.

The core parts of a blockchain that you can try your hands on include smart contracts, decentralized apps, and ICOs (Initial Coin Offerings). Start slow, master a small section of blockchain development, and gradually move on to bigger and greater things. As you learn, you will be exposed to more programming languages like Solidity, one of them being GO. It makes sense to get familiar with these languages once you are comfortable with languages like Solidity. 

So, the journey to becoming a blockchain developer isn’t as hard as it sounds. Start off slow, learn some languages, apply them to projects, and keep moving forward!

Sites and tools for competitive programming

As a coder, you should not be satisfied with just reading and coding on your computer. For developing your coding skills, you need to test yourself. You need to take yourself outside your comfort zone and evaluate how you perform. That’s what different coding competitions do for you. As you compete for a prize against several experienced coders, you can really feel the heat of coding under pressure. Plus, it will push you to execute shorter and quicker codes, enhance your problem-solving skills and make you a much better coder than before.

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You might be already planning to take part in a coding competition. Well, competitive programming is not easy. However, many sites and tools on the internet can help you with your coding and mould you into a good contender for the first prize in any coding competition. Here are the sites that can help you develop or improve your coding skills:

Topcoder

This is a US site which hosts 1.5-hour Single Round Matches.Topcoder has a specialty along with hosting these matches: they even host Topcoder Open tournament every year. On top of that, you also get tutorials written by respected and experienced Topcoder members. 

HackerRank

HackerRank is a famous site for people aspiring to participate in coding competitions. The site is focused on competitive programming challenges, hosting CodeSprints, 101 Hacks, HourRanks and Week Of Code contests every month. It even provides the learning tracks of different programming languages and topics.

CodeChef

CodeChef is an Indian site which hosts 3 contests every month. It has a Long Challenge, which is a 10-day challenge, a shorter Cook-Off challenge and Lunchtime Challenges. For beginners, the Long Challenge is a great place to start. CodeChef also organizes the CodeChef SnackDown coding competition every year.

HackerEarth

This Indian company focuses on hiring challenges and competitive programming. It conducts Circuits every month and shorter challenges called HourStorms. Circuits are generally 9-day long. HackerEarth hosts competitions in several colleges all over the country too.

Tools

During programming contests, you can use a number of tools to debug a problem or highlight a problem. These are a few tools that can be really helpful for you:

Online IDE’s

  • Ideone – This is a commonly used sharing and testing code. You can easily make an account and save your programs here. However, it does not show the execution time of a program.
  • Codechef/Rextester/Codeforces: Unlike Ideone, these sites will also show the execution time of your programs. With Rextester, you can even develop an execution command for your program too.

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  • CSAcademy IDE: This IDE has all the features of the previous IDE’s along with a workspace which helps you to work on several files simultaneously. This IDE has a ‘stderr’ stream too, so you can debug statements using ‘cerr<<’ debug statements.
  • HackerRank IDE: This IDE can be used on its problem pages. An advantage it has over other IDE’s is that it can display the gdb stack trace when there are runtime errors. Hence, you can understand which line the specific segmentation error occurred. 

Difference Checker

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Stress testing is a great way to find out a bug in an algorithm. Stress tests mean to generate a large set of random test cases and then, to check if the efficient algorithm and the brute force algorithm agree with one another. The tools that can be used for this are: CSAcademy Difftool and Diffchecker.

Online Debugger

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You can use OnlineGDB for debugging the code. It is a compiler and is also a debugger for a number of languages.

Online Formatters

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If you want to share your code so that others may look at it, it is best to format it in a way that makes it easy for others to read it. Online code formatters are a great way to go. Some online code formatters are: format.krzaq.cc, CodeBeautify formatter and the TutorialsPoint formatter.

Visual Tools

If you are not able to visualize a problem properly, you can use Geometry Widget and Graph Editor.

You can use VisuAlgo for featuring animations for algorithms and data structures.

You can also visualize data structures, operations and algorithms using Algorithm Visualizer.

Problem Archives

Browsing through Archives can be a great way to enhance your coding skills. Here are a few archives that you can go through:

SPOJ

This archive consists of several solved classical problems as well as discussion forums. It is a great archive for beginners.

UVa OJ

UVa OJ is a famous archive with more than 3500 programming problems. This archive is generally used with Competitive Programming 3 textbook written by Steven and Felix Halim. 

A2 OJ

This archive has thousands of problems but the best part is that they are divided as per their category. You can even learn a new skill and go through problems related to that. This archive also features Codeforces ladders. In Codeforces ladders, you can join the ladder based on your Codeforces rating. You can then solve the necessary problems required for your skill level.

Project Euler Archives

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This is a great archive to challenge your coding and mathematical skills. You will face a series of challenging problems, whose difficulty will increase as you proceed further. It’s a great way to take you out of the comfort zone.

Google CodeJam Archives

In this archive, you will face the problem of Google CodeJams from previous years.

If you wish to get proper training on competitive programming as well as code in a competitive programming environment, then you should enroll yourself in a course. Coding Ninjas has a great course designed only for coders who want to participate in coding competitions. It has an ongoing leaderboard to evaluate your submission and is powered by Codezen, a great online coding platform. Plus, it’s Online!

Use these tools and sites and get an edge in the coding competitions. Best of luck.

Your ultimate cheat sheet to do’s and dont’s at an interview

Is there a magical formula which cuts into the interview and gets you hitched with your dream job? Nope, none as yet but what you do have is a set of do’s and don’ts which should which helps you to ace the interview. So let’s take a quick look at them:
do

Dress well: An interview is a formal meeting, you will get judged by your clothes. You cannot just expect the interviewer to applaud you if you walk in with your checkered boxers and crappy hair. Dress well, be poised not too gaudy neither too shady just a mix of decent colors and what suits you well. You may cross my statement by saying startups these days do not care what you wear. Of course, there is casual clothing allowed at startups and big firms too but you are going for a job interview, not a pool party!


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  • Plan to arrive early: Getting to the venue at least half an hour early is always a plus. First, you do not have to panic about getting late and second getting used to the surroundings and people calms your nervousness down.

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Have a firm handshake: Your first impression is the last impression. Walk into the room with grace and your head held high. There is nothing to be ashamed of, walk in your stride and have a firm handshake with the interviewers.


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Tailor your resume and conversations well: Your resume should be ready to suit the job description. Same goes for your conversations do not talk or mention irrelevant stuff. Have contextual conversations around the skills and job. The interview is about you and your skills and you should leave no stone unturned to tell how you’re a perfect fit. Talk about your experiences and recent internships, get them interested into what else you do outside the box.


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Ask questions: Do not hold yourself back. Your inquisitiveness may be the road to your success. When the interviewer asks you whether you have any questions or not, do not shy away. Ask about the company, ask about your job make them feel you’re actually interested in the job. If you get a chance to take their mail id or so, write back to them about the great experience you had.


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dont
  • Do not overdress or underdress.
  • Never-ever-ever be LATE for an interview, puts your punctuality and sincerity at stake.
  • Being confident is good but over confident is not.
  • Retrain from blabbering, listen carefully and answer. It’s okay if you do not know an answer, beating around the bush and wasting both your and interviewer’s time is not a good move.
  • Do not be afraid, the interviewers will not beat you up. I know this is easier said than done. I’ll give you a quick tip- look at the interviewers while talking but defocus them or look at the gap between two eyes. This ensures eye interaction and also does not make you nervous.
  • Do not have a lanky posture and do stuff like moving your legs and rubbing your hair. Walk on your heels, do not drag. Sit upright, no crossed legs or folded arms.
  • Do not be casual and use the jargons we millennials use every day in our lives. No ‘I wanna’, ‘I Gotcha’, ‘Sumfin’ or facebook and Whatsapp language are permitted. Be careful of what you speak.
  • Do not let your talks go haywire. eg. You are applying for a data analyst position and talking about your in-plant industrial skills will not be making sense. Have contextual talks, add your own elements and make it interesting.
  • Don’t inquire about salary, vacations, bonuses, retirement, or other benefits until you’ve received an offer.
Atta boy, soldier! Confident much eh? Wait until you nail your next interview!
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