Hi, I’m Sina Torfi.

I am the founder of the Machine Learning Mindset. My ultimate goal is to promote AI and Machine Learning to make an impact. [Twitter, GitHub, LinkedIn]

Only on GitHub, my open-source projects have 10,000+ monthly readers and 5000+ developers are currently make benefit from them. I write about Machine Learning and Deep Learning. My projects were featured and trending on GitHub and Hacker News many times.

On the Importance of Open Source Science

My full name is Amirsina Torfi (my nickname is Sina and it may look much easier to call than Amirsina! Right?), and I am a researcher and developer that dedicated my professional life to Artificial Intelligence, Machine Learning, Deep Learning and their application in various domains such as Computer Vision, Natural Language Processing, and Healthcare.

I have devoted my time to open source and educate developers and taken many various projects to the state of being GitHub trending repositories per day, week, and month. In case you are not familiar with GitHub, I should say it is the world’s leading software development platform which everything in Machine Learning and AIwhich is open source, happens there! 

Working as an open-source developer was great because you will soon understand what you do NOT know! During my years of experience as an open-source developer, I learned a crucial lesson: If we just listen to others’ experience and knowledge, little by little, we start to become an expert! There is a downside though: If we hear too much, we forget our uniqueness and lose the way! Finding that trade-off is our job.

I had a lot of moments trying so hard to learn a concept in Machine Learning and Deep Learning. What was missing?

I realized the problem was not knowing some simple concepts deeply! The secret sauce to understanding is to break a complex concept into its simpler constituent elements. So I started a blog to explain all those simple basic concepts that NOT knowing them lead to wasting a lot of time digging and searching!

And now, I am mostly doing …

CONSULTANT

Helping others who are trying to use AI and Machine Learning and looking for insightful solutions.

BLOG

Serving the community by teaching the important concepts in Machine Learning and Deep Learning and open sourcing.

RESEARCH

I am a Deep Learning researcher. I am working on the application of Deep Learning in Natural Language Processing and Healthcare.

Starting of My Journey

From disappointment to the aspiration and success …

I will keep it short for now…

I am going to share with you some short personal story and give you some advice (friendly and/or professionally) about how to start and become an expert in Machine Learning.

When I started my Machine Learning journey in 2016, I knew nothing literally! I did not know anything about Python, TensorFlow, Deep Learning, or any other buzzword related to Machine Learning, whether it was a concept or a framework. My Ph.D. advisor back then used to blame me frequently about why I do not know anything in that regard. It’s funny. Right? I just started, and my background was Electrical Engineering. I do not know how my advisor thought I should know everything as I was just started! It usually happens. Right? Someone blaming you, and you do not understand why or you are 100% sure what they say does not make sense. After a while, I realized he was right about some aspects (and not all for sure)! I was not spending enough time. Simple!

I was working hours and hours to learn more and more. After a few months, I became someone average from being a complete idiot! You may wonder how? The answer is simple: I did not overthink about if I can or cannot do it; I just did it. I just continue learning. Until after two years of hard work, something happened. My GitHub project titled TesnorFlow World (my first successful project after tens of complete failure!) became the GitHub trending project of the day, week, and month.

That was the start of me becoming confident that I can make an impact!

Then I developed many successful projects, all started after witnessing the hard work, works!!

The 10-day visitors’ statistics regarding one of my open-source projects titled Machine Learning Course. The blue line shows unique visitors. Date: December 2019.
The 10-day visitors’ statistics regarding one of my open-source projects titled TensorFlow Course. The blue line shows unique visitors. Date: December 2019.

That’s all! The followings are some of my personal thoughts on how to start and proceed:

1. Set goals that you don’t believe are too ambitious.
Machine learning is too broad, and it has a lot of different aspects. You cannot wake up, and all of a sudden, decide to over-kill it! It will look too powerful to beat in your eyes. Start with some realistic goals. A great example is as follows: I want to finish a great online course (suggestion: Coursera Machine Learning Course).

2. Do not expect too much of yourself at the beginning.
Why are you in a hurry?! You cannot expect yourself that after three months of practicing, you master a new skill! You simply CANNOT. Start with core concepts. Give yourself some time. Don’t be tough on yourself.

3. You need both theory and practice.
You don’t have to read the theory of a concept and understand every detail. One the other hand, you do not have to do practices spoon-by-spoon. BUT, you need both theory and practice. You cannot skip any of those entirely.

4. Write simple algorithms by yourself.
DO NOT try the hard ones. Start with simple and core algorithms. It helps you to think more algorithmic. Our brain needs some practice. When we start to write simple core algorithms, not only we learn more, but also it increases our self-esteem as we tell ourselves: I DID IT!

5. NEVER compare.
Do NOT compare yourself with anyone else. Don’t judge your intelligence or power of will. PRACTICE MAKES EXCELLENCE! I bet you heard that. Right? You should not. You do not know the whole story of anybody else. You cannot blame yourself just because you believe you are dumb in Machine Learning. If you think so, not only you are wrong, but you are missing the point: Have you tried it? Work for 100 hours, and you see how better you got. Work for 1000 hours, and you are an absolute expert. Work for 10000 hours, and you are UNSTOPPABLE!!

Should you follow this blog?

I explain the strong points and the decision is ALWAYS yours…

  • The GitHub repository associated with this blog is ranked as the top 300 GitHub accounts worldwideThis is NOT because I am a good coder! NOT at all! There are many developers out there doing that better than me for sure! I have that honor because I learned how to build a project and educate others about what I know and understand. I got to the point that realized maybe a blog is the best way to share my knowledge and use other knowledgeable people’s experience to learn.
  • In this blog, we are going to provide you with step-by-step instructions on how to understand and implement different crucial concepts in AI and Machine Learning. You can start from almost zero and get it to advance, along with my step-by-step tutorials and ebooks for everyone, especially beginners who have the desire to start with minimum wondering about the useful materials.
  • I am interested in sharing my knowledge. That way, I can learn better as well. It happened to me numerous times that someone gave me feedback or asked me a question and made me ponder about my knowledge again. Sometimes I ask myself, wait a second? Are you sure? Can I do better or differently?” I like to question myself. Don’t make me wrong! It is helpful if we challenge ourselves constructively. Let me bring up a life-changing quote:

““THE FIRMER YOUR GRASP ON REALITY, THE MORE POWER YOU WILL HAVE TO ALTER IT FOR YOUR PURPOSES.” 

― 50 Cent, The 50th Law

Vision

What is the vision of this blog and our pledge…

This blog aims to provide the knowledge to become a master in Machine Learning. The goal is to bring insight from scratch without any assumption on the technical level of the readers. If you found it otherwise for any post, let us know by sending us your feedback. We are open to change!

Your interest is piqued? please continue…

Let’s see what we commit and what you can expect.

Our pledge

  • We provide insightful posts in Machine Learning and Artificial Intelligence that help you to learn concepts.
  • Your feedback and comments are much appreciated and NOTHING will be ignored! However, forgive us for possible delays.
  • No more than two or three emails per week! No one wants to be disappeared in the cloud!

Interested to stay tuned?

By subscribing to our blog, the following benefits are waiting for you:

  • You will receive exclusive materials that are NOT available on the blog publicly such as the fully functional source code regarding an explained concept on the blog.
  • You will receive exclusive materials that are NOT available on the blog publicly such as the fully functional source code regarding an explained concept on the blog.
  • Free materials only available to subscribers.

ALWAY Stay Tuned…

StayInformed...

Sign up to our mailing list to receive tips and tricks on AI and Machine Learning. Join us at Machine Learning Mindset and you will learn where to start and how to become a master.

Related to Machine Learning and Deep Learning, contact us if:

  • You want to develop a project and wondering where to start.
  • You desire to master a topic and looking for associated resources.
  • You need help with your questions about a technical concept.
  • You desire to grow your project.
  • You want to write about technical content.
  • You need specific ideas in your application (Computer Vision, Natural Language Processing, Speech Recognition, and Healthcare) to test.
  • You need consultants about the overall strategy and implementation details.

Please feel free to contact us with your inquiries.

Thank for your interest and time that you kept READING up to here…

Let’s learn together and help each other grow.

Thank you so much for your interest. If you had any questions, send me an email at [email protected]. I would be more than happy to speak with you.

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