Author DP

Prabhav Phalgun

2+ of articles published

Creative Mind / Wise Guide / Artistic Soul

Domain:

upGrad

Current role in the industry:

Co-Founder at UpGrad.com

Educational Qualification:

Bachelor of Technology (B.Tech.) in Civil Engineering from Indian Institute of Technology, Delhi

Expertise:

Management Consulting

Analytics

Financial Modeling

Business Strategy

Business Analysis

About

With 7 years of education experience across different geographies, Phalgun leads the overall growth operations and university relations at upGrad. Phalgun is an alum of IIT-Delhi and part of the Forbes 30-under-30 cohort.

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Relevance of Machine Learning in the Cloud
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5121

Relevance of Machine Learning in the Cloud

We at upGrad have recently launched an Advanced Certification Program in Machine Learning & Cloud with IIT Madras. I have received a lot of queries from prospective learners about why we chose to teach these two skills and the below article is an attempt to explain the power of Machine Learning in the Cloud.  Top Machine Learning and AI Courses Online Master of Science in Machine Learning & AI from LJMU Executive Post Graduate Programme in Machine Learning & AI from IIITB Advanced Certificate Programme in Machine Learning & NLP from IIITB Advanced Certificate Programme in Machine Learning & Deep Learning from IIITB Executive Post Graduate Program in Data Science & Machine Learning from University of Maryland To Explore all our certification courses on AI & ML, kindly visit our page below. Machine Learning Certification Two Primary Barriers: There are two main roadblocks for the widespread application of machine learning. One, competence and the second, cost. And herein lies the power of machine learning in the cloud. Most references to machine learning involve the Netflix recommendation engine or the Uber autonomous car or some other grand project. But for me, one of the most inspiring applications of machine learning is the less heard story of the Japanese farmer who used deep learning & TensorFlow to sort his cucumbers! He used machine learning to save a significant amount of manual effort without any prior knowledge of the subject and with very limited investment. This is an example of the true democratization of machine learning and the potential it has to improve the status quo, for everybody. 1. Competence: First, let us address the question of competence. We have all heard of the “lack of talent” in the area of machine learning. While we continue to train more people to become machine learning experts, it is also equally important to simplify the process of applying machine learning. Cloud service providers like Amazon, Google & Microsoft have set up powerful systems to help build, train & deploy models with relative ease even if you do not have any expertise in the area. Pre-existing libraries can now be deployed for data processing, model building/ training/ evaluation/ deployment, leading to accurate predictions & recommendations. This greatly reduces the requirement for millions of machine learning experts to drive adoption & impact.  Trending Machine Learning Skills AI Courses Tableau Certification Natural Language Processing Deep Learning AI 2. Cost: Second, the question of cost. Deploying machine learning algorithms requires a lot of computing power and hence a large scale hardware infrastructure. Let us take the example of our Japanese farmer, who ran the neural network models on his Windows PC. Even after converting the images to low resolution, it would take up to 3 days to train the model with 7000 images! Using a larger number of high-resolution pictures would significantly improve the accuracy, but would also drastically increase the training time with the computing power of a Windows PC. In more advanced settings with real-time training/ prediction and fluctuating loads, the computing power requirement is very high and costly. This issue can be addressed by using low-cost cloud platforms for training/ prediction that dedicates hundreds of cloud servers to training a network via large scale distributed training. In this model that is now fairly standard, you can avoid large upfront capex investment, have flexible computing capacity and only pay for what you use. Cloud service providers have basically reduced the entry barrier for machine learning by reducing the level of competence & cost required to use it effectively. For all applications like autonomous cars, IoT, smart connected homes and even for cucumber sorting, understating how to use the cloud infrastructure to effectively develop, train & deploy machine learning models is an important skill to master.  Popular AI and ML Blogs & Free Courses IoT: History, Present & Future Machine Learning Tutorial: Learn ML What is Algorithm? Simple & Easy Robotics Engineer Salary in India : All Roles A Day in the Life of a Machine Learning Engineer: What do they do? What is IoT (Internet of Things) Permutation vs Combination: Difference between Permutation and Combination Top 7 Trends in Artificial Intelligence & Machine Learning Machine Learning with R: Everything You Need to Know AI & ML Free Courses Introduction to NLP Fundamentals of Deep Learning of Neural Networks Linear Regression: Step by Step Guide Artificial Intelligence in the Real World Introduction to Tableau Case Study using Python, SQL and Tableau If you are interested to learn about cloud computing and Machine learning, upGrad in collaboration with IIIT- Bangalore, has launched the Master of Science in Machine Learning & AI. The course will equip you with the necessary skills for this role: math, data wrangling, statistics, programming, cloud-related skills, as well as ready you for getting the job of your dreams.

by Prabhav Phalgun

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30 Sep 2019

The Difference Between Free and Paid Online Programs, Explained!
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7054

The Difference Between Free and Paid Online Programs, Explained!

Disclaimer: I refer to paid programs as a standardised product. I am painfully aware that there is a huge fluctuation in the quality of paid online program offerings, but I commit this transgression to simplify and broadly establish the differences between paid and free online programs. Mainstream awareness of online education was built via MOOCs (Massive Open Online Courses) and hence, a lot of people assume online education = free. When making a purchase decision, they struggle with understanding the cost-benefit analysis of paid online education. While attempting to explain the difference between paid and free online learning, I will simplify for the sake of brevity. The key difference between free and paid programs is the following: Enrolling in a free program is like buying a library membership vs. enrolling in a quality paid program is like getting admitted to a top-class university. The purpose of academic learning is to build your confidence and help your career progress. When you get a library subscription (free online course) you will buy access to a large pool of materials, but to achieve your objective you need to do the following: Have the self-discipline to go to the library   Have the self-awareness to know what books you want to read – why and how?   Have the self-discipline to complete the books you have picked up   Rely on self-guidance (Google!) to resolve all your queries   Create the self-image of having credible skills when you meet someone The Verdict on Online Courses: To Do or Not To Do When you have to rely so much on yourself, without social support or inspiration, you know that it is not going to end well, 99.9% of the times. When you get admitted to a top class university (quality paid online program), you have access to: A structured curriculum and tangible learning outcomes   Experienced faculty teaching you academic concepts   Hands-on application projects   Amazing peer network   Industry mentorship and career assistance services   A reputed certification/credential with broad acceptance Infographic: What After IT? Top 5 Transitions You Can Make Our Top Data Science Programs & Articles Masters of Science in Data Science from LJMU & IIIT Bangalore Executive PG Program in Data Science from IIIT Bangalore Professional Certificate Program in Data Science for Business Decision Making from IIM Kozhikode Professional Certificate Program in Data Science and Business Analytics from University of Maryland Master of Science in Data Science from University of Arizona Data Science Vs Data Analytics: Difference Between Data Science and Data Analytics Advanced Certificate Program in Data Science from IIIT Bangalore Advanced Program in Data Science from IIIT Bangalore Data Science Career Growth: The Future of Work is here Our commitment, within all UpGrad programs, has been to provide our learners with all of the above, via our academic and industry partners. This has helped us achieve >90% completion rates and successful career transitions for many UpGrad learners. Hence, UpGrad learners compare the programs with other Post Graduate/Masters programs and not free online programs. Have you tried an UpGrad program yet? Get on the fast track to upskilling by clicking below!

by Prabhav Phalgun

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07 Feb 2018

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