Machine learning as a career (in India or abroad)

In summary, the individual is interested in pursuing a PhD in machine learning, but has concerns about their background in mathematics and programming. They are specifically interested in using machine learning for automatic music composition and classification. The expert recommends having a strong background in statistics and learning C and C++ for this field. They also advise being able to read and modify code to effectively use machine learning tools.
  • #1
dexterdev
194
1
Hi all,
I recently got very interested in machine learning and neural networks etc. Although I am having a taste for mathematics , I haven't rigorously learned any mathematics course because my background is electronics engineering (masters level). And also I am not a good C or Java programmer. My basic doubts are :

1. Is heavy math prerequisites needed for me to do a Phd in machine learning? (Or can the required math can be learn from phd course work itself)

2. Should I require great programming skills in C / C++ / Java / Python etc for machine learning? (What I can handle at the moment is Matlab or Octave etc)

My some of the research dreams is to work on automatic music composition, classification etc.
Please guide me in this area.

-Devanand T
 
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  • #2
Hey dexterdev.

With regard to automatic music composition, you should take a look at applied probability models like markov and hidden markov models.

As for machine learning, you should (in my opinion) get a decent statistics background so that you understand what is going on with things like naive Bayes, neural networks, and other classifications based on statistical models.

You will also need to read code at some point and take other peoples code to compile. If you don't know how to program then things are going to be difficult.

If there is a bug in the code or you have to start changing variables or code definitions to get the kind of behavior that you need, you are going to be stuck.

I would recommend you learn C and C++ for this field.

The thing that you need to answers is whether you are justing going to use the tools as is, or whether you are going to modify, create, and apply the tools for a variety of situations in different ways.
 
  • #3
Thanks for the reply Sir.
 

1. What is machine learning?

Machine learning is a subset of artificial intelligence that involves using algorithms and statistical models to allow computers to learn from data and improve their performance without being explicitly programmed.

2. What are the job opportunities in machine learning?

The job opportunities in machine learning are vast and diverse. Some common job roles in this field include machine learning engineer, data scientist, data analyst, and AI researcher. These roles can be found in various industries such as technology, healthcare, finance, and retail.

3. Is it necessary to have a background in computer science to pursue a career in machine learning?

While a background in computer science can be helpful, it is not always necessary to pursue a career in machine learning. Many individuals with backgrounds in mathematics, statistics, or other related fields can also enter this field with the right training and skills.

4. What are the skills required for a career in machine learning?

Some essential skills for a career in machine learning include programming languages such as Python and R, knowledge of statistics and mathematics, data analysis and visualization, and familiarity with machine learning algorithms and techniques. Strong problem-solving and critical thinking skills are also important in this field.

5. How can I start a career in machine learning?

To start a career in machine learning, you can begin by learning the necessary skills through online courses, workshops, or self-study. It is also beneficial to gain practical experience through internships or projects. Networking and participating in machine learning communities can also help you stay updated on the latest developments in the field and connect with potential employers.

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