Rajeev Kanth’s Post

Founder & CEO, BEPEC Solutions | Worked with 50+ Companies as Data-Driven Strategic Consultant | LLMs | Generative AI | ML | DL | MLOps | Azure Data Engineering | Power BI | Snowflake | Kafka | AWS

3mo

Step By Step Guide To Become AI Engineer 🤖 If you are looking for personalised 1-on-1 Roadmap Call, You can book a call with me!! Link in Bio #artificialintelligence #ai #machinelearning #naturallanguageprocessing #deeplearning #datascience #dataanalytics #statistics #probability #python #programming #devops #mlops #datascientist #aiengineer #jobshiring #careertransition #careerdevelopment #kanth

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To be an AI engineer, you need to focus on Python. So in Python especially, you need to focus on Pandas, Numpy, Cyclone, and even Tensorflow Pytorch related libraries. And after completion of that, you need to focus on your statistics and probability. And then you need to jump into your machine learning algorithms, Be very good with your machine learning algorithm math, and even try to work on some projects on machine learning and natural language processing. Once you've completed that within natural language processing, focus on Word to work. Will focus on topic modeling so within a topic modeling we have LDA, so like dependency parsing and all these concepts once you've completed an LP, then get into deep learning so like where we work on feed forwards, computer vision, LTMS, RNS, so Gans and your restricted Boltzmann machines, so diffusion models, normalizing flow models and this way we have the concepts and then get into generative AI. So all these concepts you just need to focus on end to end deployment using AI OPS pipeline or Mellops pipeline that. Going to help you to secure a job in lines of artificial intelligence.

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Step By Step Guide To Become AI Engineer 🤖 If you are looking for personalised 1-on-1 Roadmap Call, You can book a call with me!! Link in Bio #artificialintelligence #ai #machinelearning #naturallanguageprocessing #deeplearning #datascience #dataanalytics #statistics #probability #python #programming #devops #mlops #datascientist #aiengineer #jobshiring #careertransition #careerdevelopment #kanth
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One of the most useful skill sets I have learned in my career as a Data Scientist & ML/AI Engineer, might not be the first thing you would expect. Care to take a guess? That skill set is debugging 🐞! Yes, that’s right debugging! The ability to quickly determine how, where and why your code is failing. My main language is Python 🐍 and I am going to share a few commands, but this extends well beyond Python. Become a master debugger in your language. In Python, you may already have an idea of what may be happening after observing your stack trace. Placing a simple import pdb; pdb.set_trace() at the approximate location in your code, you can run the code until you find your error. There is also another useful feature in Jupyter and ipython. Let’s say you are running some code you imported and one of those pesky bugs come up but you have no idea what is happening. There is a command that you can use after the bug appears, %debug . Sometime this takes you right to the source of the problem and sometimes you may have to go up through the stack trace until you match the error with the failed line of code. Then you can investigate 🕵️♂️ until you find it. Bug gone! 🪲❌ #datascience #datascientist #ai #aicommunity #aiengineer #aiengineering #machinelearning #datasciencejourney #datasciencecareer #dataleadership #datalearning #mlengineer #machinelearningengineer #debugging #debug #softwareengineering #softwareengineer #softwaredeveloper #mlops #skillup #skilldevelopment #skillbuilding #skillenhancement #dataengineering #dataengineer
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Rajeev Kanth

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