Deep learning vs machine learning

Deep learning vs machine learning

Machine Learning and Deep Learning are two approaches to building AI that have generated a lot of buzz recently, both among tech companies and on university campuses worldwide. But which kind of AI should you focus on? Should you opt for a Deep Learning course or a Machine Learning certification? The answer lies in your career aspirations and the type of projects you want to work on. In this article, we’ll break down the differences between machine learning and Deep Learning and discuss when you should use each type of technology based on your career goals and interests.

What is Deep Learning?

Deep Learning is a branch of machine learning that models high-level abstractions in data and understands complex data with multiple levels of representation. Deep neural networks have been successfully applied to supervised and unsupervised problems and can be used as feature detectors or classifiers. Thus they are capable of performing inference in higher layer neural areas. They have been used on large-scale problems for information retrieval, speech recognition, and computer vision, producing results comparable to humans.

What is Machine Learning?

Machine Learning makes computer software more accurate in predicting outcomes without being explicitly programmed. Instead, ML relies on statistical techniques, including regression and classification. It allows computers to learn from past data and predict future events based on those learnings. The basic idea behind machine learning is that you use algorithms to train your system to recognise patterns in your data. Once you’ve trained your system, you can use it for prediction tasks such as forecasting demand for products, recommending products or services, identifying potential customers, and detecting credit card fraud. 

The difference between Deep Learning and Machine Learning

Deep Learning refers to a subset of Machine Learning algorithms. Multiple layers of nonlinear processing units characterize it for feature extraction and transformation. In contrast, Machine Learning refers to any form of Artificial Intelligence in which a program ingests data and learns from it. There are two types of machine learning algorithms – Supervised and Unsupervised. Supervised learning requires input features and their desired output values, whereas unsupervised learning doesn’t require any desired output values but uses input features only. 

Challenges in learning Deep Learning and Machine Learning

Deep Learning is rapidly evolving, with breakthroughs in neural networks being published frequently. But at its core, it is just another type of Machine Learning, albeit one that has proven to work very well on many problems. So why use Deep Learning vs other forms of Machine Learning? If a problem can be solved using linear methods and the output benefits from taking advantage of an entire nonlinear pipeline, it would probably be best to stick with that method. However, many interesting problems—like detecting complex patterns in images or text—are hard to express as equations but are easy for humans to make intuitive sense.

Deep learning allows us to take advantage of our intuition about how we want these problems solved. Deep Learning also provides a way to learn representations for data automatically, which is especially useful when there isn’t a precise mapping between input and output. Instead of building those mappings manually, we let our model figure out what features matter most, making Deep Learning ideal for applications like computer vision, where feature engineering is difficult or time-consuming. The critical question here is – is lots of labelled data needed? 

Challenges in the future

Artificial intelligence is taking off, with new developments advancing every day. It’s no longer a matter of if AI will be a part of our lives but rather when. Machine Learning is currently happening—and fast. The advancement of Deep Learning research has brought us close to computers that can learn how to learn, such as AlphaGo and IBM Watson. Deep Learning is challenging many professions, raising concerns about robots and machines replacing jobs. As with any technological advance, we need to consider many pros and cons before diving into a future powered by artificial intelligence. So let’s look at some areas where Deep Learning is transforming business today. 

Applications of Deep Learning

Deep Learning has a broad range of applications, including information processing, various forms of data mining, and knowledge discovery. It is also used for fundamental studies on understanding natural language processing and further help in semantic parsing. Self-driving cars and robots are other fields where Deep Learning plays an important role. It enables computers to master many complex problems without being explicitly programmed to solve them—and sometimes even without being told what they are supposed to accomplish. Applications of Deep Learning include image recognition systems like Google’s image search; speech recognition systems like Apple’s Siri; natural language processing systems like Facebook’s automatic tagging system; recommendation engines like Amazon’s product recommendations; autonomous vehicle control systems like Tesla’s autopilot mode; medical diagnosis systems like IBM Watson etc.

Conclusion

Deep Learning and Machine Learning seek to help computers think and make decisions differently. Deep Learning seeks to replicate human brain function, whereas Machine Learning emphasizes efficiency. Deep Learning and Machine Learning differences are subtle yet essential in determining when you should use each. In addition, while they may seem similar on paper, some critical distinctions between these fields can affect their implementation in real-world applications. 

If you want to build an enriching and fulfilling career around Deep Learning and Machine learning, the best way is to learn artificial intelligence from experts. CERTIFICATION IN ARTIFICIAL INTELLIGENCE & MACHINE LEARNING offered by Imarticus Learning. It is an advanced industry-approved program designed by E&ICT Academy, IIT Guwahati, for future data scientists and machine learning engineers. For any queries or guidance, contact us through chat support, or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad. 

From zero to research- An introduction to IIT AI/ML course

AI & Machine Learning in Everyday Life

The importance of Artificial Intelligence (AI) is constantly on the rise and so is its involvement in our everyday lives. Although we don’t often think about it, AI is everywhere.

From chatbots that communicate with us on various online shopping platforms and websites to social media platforms that target audiences and advertise products based on our searches, AI is encoded everywhere. Being such a pertinent part of business, these days makes enrolling in an artificial intelligence and machine learning course a viable option to ensure a lucrative offer in the job market.

Here are 8 ways AI is present in our everyday lives without us even noticing:

  1. Face recognition locking on our phones
  2. Friend suggestions, product/service advertisements based on searches on social media
  3. Spell checkers and Grammarly tools installed on emails and messaging portals
  4. Google searches
  5. Voice assistants such as Siri and Alexa
  6. Smart home devices such as air conditioning machines, electrical switches, refrigerators, and so on
  7. Google maps and other satellite-based trackers
  8. Content suggestions on Netflix based on your watching history

IIT AI/ML Course

Given the way AI is becoming a part and parcel of our lives, the Indian Institute of Technology (IIT) is offering AI/ML specialized courses so that you can gain in-depth knowledge and skills in the applications and techniques associated with machine learning. The idea is to upskill professionals and train them in a manner so that they are ready to take on high-paying jobs in the world’s most demanding computer language.

These are certificate courses that span over a period of 6 months and during this time you will be taught the following subject areas:

  •         Basics of Python
  •         Mathematical Background
  •         Introduction to Machine Learning
  •         Regression Analysis
  •         Optimization in ML
  •         Unsupervised Learning
  •         NLP and text analysis
  •         Feature Selection and Dimensionality Reduction
  •         Reinforcement learning

Outcomes of the Program

  •   Are able to quickly and relevantly gather insights by analyzing data
  • Are able to come up with predictive models that use decision trees and neural networks
  • Can carry out mathematical operations on an array of data
  • Are skilled enough to operate Pandas so that you can manage data, rearrange them and carry out various kinds of analysis
  • Can create text classifications systems making use of learning methods and linear classifiers
  • Professionals can compare optimization techniques and how they effectively solve learning issues across platforms and models to reduce the extent of errors

Who Can Apply for the IIT AI/ML Course?

The artificial intelligence and machine learning course is perfect for anyone keen on learning about machine learning.

Additionally, this program is the right fit for professionals who understand computer programming language and has completed their graduation with preferably a year of practical experience in the industry. You will find this course if you:

  •         Are tasked with machine learning projects or software development
  •         Wish to be at the helm of machine learning projects or want to work in this field
  •         Already have practical knowledge of programming languages such as C, C++, and java

Why Should You Go for this Program?

When you enroll in the artificial intelligence and machine learning course at IIT, you are to get the following benefits:

  • Get a chance to learn and earn a degree from the country’s best engineering school
  • Get a chance to participate in interactive online learning sessions which will be in live mode
  • Will be able to interact and exchange ideas with the best faculty comprising of the top industry professionals
  • Engage in productive peer-to-peer networking and learning
  • Build a strong foundation in concepts such as high-level Python programming, AI, and ML 
  • Participate in the biggest placement on-campus drive

Conclusion:

The importance of artificial intelligence and machine learning courses will continue to be on the rise given the greater involvement of AI in our daily lives. From healthcare, banking, financial institutions, gaming & entertainment to the airline industry, AI is a necessity, and enrolling in the IIT AI/ML course will equip you with industry-specific skills that will help you in every aspect of your professional life.

Bring ideas to life, drive economic growth and expand human welfare with AI courses

AI courses are a great way to bring your ideas to life and expand human welfare. With AI, you can create new products or services that improve the quality of people’s lives. You can also use AI to automate processes and tasks that used to be done by humans.

It can help businesses save money and increase efficiency. In addition, AI can help researchers solve complex problems and discover new cures for diseases. By taking an AI course, you will have the skills needed to make a difference in the world! 

What is AI, and how will it change the world economy?

The future of AI is so bright we have to wear shades. That’s because the impact of artificial intelligence on economic growth promises to be enormous and far-reaching. The Mckinsey & Company reports that “by 2030, AI could deliver an additional global output of around $13 trillion – or about 16% higher cumulative GDP compared to today.”

That’s a pretty staggering number, and it underscores the importance of getting up to speed on AI for personal and professional reasons. And that’s where our new AI courses come in! They cover all aspects of AI, from its history and development to the latest applications. 

How can AI courses help people learn new skills and advance their careers?

AI can increase business efficiency by automating menial tasks and improving decision-making. By taking AI courses, businesses can learn how to use these tools to improve their productivity. In addition, as artificial intelligence becomes more widespread, employees who are familiar with its workings will be in high demand.

By teaching them how to use AI in everyday activities, AI courses can also help people improve their lives. For example, an AI course may teach students how to identify and correct errors when they see them or create a chatbot that can intelligently respond to questions.

The benefits of artificial intelligence for human welfare

Artificial intelligence is a new technology that many industries have adopted to increase efficiency and creativity. For example, AI can help us make better financial decisions, improve our health and safety at work, predict the future of weather on Earth, or even what we should do in case of an emergency. Many studies have been done on AI to determine how it can benefit different areas of our lives. 

Discover AI Certification with Imarticus Learning

This Artificial Intelligence certification will provide students with a solid foundation in the practical applications of data science by teaching them how to apply their knowledge to solve real-world issues.

best artificial intelligence courses by E&ICT Academy, IIT GuwahatiThis program is for recent graduates and early-career professionals interested in advancing their careers in Data Science and Analytics, the most in-demand job skill.

Course Benefits for Learners:

  • Participate in 25 in-class real-world projects and case studies from corporate partners to gain machine learning capabilities.
  • This IIT AIML course will teach students the principles of data analytics and machine learning and expose them to several prominent tools used by professionals today.
  • Impress employers and demonstrate talents with an AIML course recognized by India’s most prestigious academic collaborations.