Hi everyone! I'm a fresher data scientist who is learning ML/AI for my next job role and I want guidance from related professionals. In this blog post, I will share my journey so far and some of the challenges I face as a beginner in this field.
I have always been fascinated by the power of data and how it can be used to solve real-world problems. I studied statistics and computer science in college and learned the basics of data analysis, programming and machine learning. I'm an undergraduate student, mainly worked on data cleaning, visualization and reporting.
However, I soon realized that I wanted to do more than just analyze data. I wanted to create data-driven solutions that can make an impact on the world. I wanted to learn how to use advanced ML/AI techniques such as deep learning, natural language processing and computer vision to build intelligent systems that can understand, interact and learn from data.
That's why I decided to pursue a career as a data scientist and started learning ML/AI on my own. I enrolled in some online courses, read books and blogs, watched videos and podcasts, and joined online communities. I also started working on some personal projects to apply what I learned and build my portfolio.
It has been an exciting and rewarding journey so far, but also a challenging one. There is so much to learn and so many resources to choose from that it can be overwhelming sometimes. I also face some difficulties such as finding good quality data sets, choosing the right tools and frameworks, debugging errors and optimizing performance.
That's why I'm reaching out to you, the ML/AI professionals who have more experience and expertise than me. I would love to hear your advice on how to overcome these challenges and improve my skills as a data scientist. How did you learn ML/AI? What are some of the best resources you recommend? How do you approach a ML/AI problem? What are some of the best practices and tips you follow? How do you keep up with the latest trends and developments in the field?
Please share your thoughts and insights in the comments section below. I'm eager to learn from you and grow as a data scientist. Thank you for reading my blog post and for your support!
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