Blog

Sai Krishna

May 9

Hi guys ,Today you were here to have a successful Timetable for Machine Learning where it is gonna be simple.Let me first introduce myself….

I am a machine learning enthusiast from India,and currently pursuing computer science in 2nd year,and a fitness freak. My journey started from c programming Language and then java, but i didn’t found interest on any of them ,but Anand an creative lecturer from Udacity inspired me to learn python.

I first took a course on Python from udacity (free cost);

Then i have done some real time projects which are needed utmost time(including web and app development)

After that i had gone through sentdex all python related stuff .

Later i was very fascinated by the Machine Learning stuff,i wanted to create fun in everything using it,so i decided to start over it,

but here comes the Biggest Problem,”what to study?from where to study?”i googled it ,as usual a bunch of hell,again in a dilemma to decide what?

so after going to all the sites and text books ,i designed a complete curriculum to get attached to all the fundamental and interesting stuff of machine learning.(Remember:”this plan only for the one who want to build products not to learn inside mathematical part”)

From above plan i have seen wonders, that never thought i could,i mean even though all those all are already solved,but rebuilding with my hands and testing on my own data set gives me much pleasure

1. PREREQUISITES: numpy , pandas, matplotlib
2. First i completed udacity intro to machine learning course free version,where it covered(most of supervised and unsupervised learning) by the end of this course you will gain knowledge of SCIKIT-LEARN
3. To understand some basic concepts of each algorithm I went through siraj raval Intro to math of intelligence simultaneously
4. After i got complete control on scikit learn ,i first completed some basic prerequisites like tensor flow basics etc. for deep learning
5. Then i took Andrew ng course in coursera,on Deep learning Specialization through financial aid ,Thanks to coursera for their help.
6. And again some siraj raval videos for practical knowledge to code.
7. then finally went on kaggle to practice more problems.

Hope you got some clarity on Machine Learning

Thank you,