Blog: Machine Learning: complete 2 months plan with free cost
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
- PREREQUISITES: numpy , pandas, matplotlib
- 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
- To understand some basic concepts of each algorithm I went through siraj raval Intro to math of intelligence simultaneously
- After i got complete control on scikit learn ,i first completed some basic prerequisites like tensor flow basics etc. for deep learning
- Then i took Andrew ng course in coursera,on Deep learning Specialization through financial aid ,Thanks to coursera for their help.
- And again some siraj raval videos for practical knowledge to code.
- then finally went on kaggle to practice more problems.
Hope you got some clarity on Machine Learning