The Background

I started Practical Deep Learning for Coders 10 days ago. I am compelled to say their pragmatic approach is exactly what I needed.

I started data science by learning Python, Pandas, NumPy, and whatever I needed in a short few months. I did whatever courses I need to do (e.g. Kaggle micro-courses) and whatever books I needed to read (e.g. Python for Data Analysis). All of this I did as a part of a 90-day MOOC’athlon learning challenge started back in April this year. It was one of the greatest learning periods of my life. After this, I completed both Iris data and Boston house price prediction projects at Kaggle. Then I scraped data from the internet and used my Pandas skills to clean them out. And implementing research papers was still confusing and frustrating. I struggled with research papers and Kaggle projects. I am good at C language. You can give me any programming language and I can learn it pretty quickly than most because programming is my 2nd nature. Computer Programming just flows in my thoughts. And this wasn’t happening with data science. Even though there were learning and a lot of work but in the end, I couldn’t remember any of what I did (yes, data wrangling is a hell lot of work). I was in a constant state of frustration. I started getting irritated at little things and it spilled into my personal life. I thought of quitting data science and machine learning. It had been 4 months and I was nowhere near having the capability to accomplish anything deemed usable for business. I felt trapped in a 4x4 feet concrete box.

#2020 oct tutorials #overviews #courses #deep learning #ai

10 Days With “Deep Learning for Coders”
1.05 GEEK