Update README.md

Author: Manash Kumar Mandal

README.md

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 <a name="general" />
 ## Miscellaneous
 - [Machine Learning for Software Engineers](https://github.com/ZuzooVn/machine-learning-for-software-engineers)
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 - [Dive into Machine Learning](https://github.com/hangtwenty/dive-into-machine-learning)
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 - [A curated list of awesome Machine Learning frameworks, libraries and software](https://github.com/josephmisiti/awesome-machine-learning)
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 - [A curated list of awesome data visualization libraries and resources.](https://github.com/fasouto/awesome-dataviz)
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 - [An awesome Data Science repository to learn and apply for real world problems](https://github.com/okulbilisim/awesome-datascience)
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 - [The Open Source Data Science Masters](http://datasciencemasters.org/)
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 - [Machine Learning FAQs on Cross Validated](http://stats.stackexchange.com/questions/tagged/machine-learning)
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 - [List of Machine Learning University Courses](https://github.com/prakhar1989/awesome-courses#machine-learning)
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 - [Machine Learning algorithms that you should always have a strong understanding of](https://www.quora.com/What-are-some-Machine-Learning-algorithms-that-you-should-always-have-a-strong-understanding-of-and-why)
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 - [Difference between Linearly Independent, Orthogonal, and Uncorrelated Variables](http://terpconnect.umd.edu/~bmomen/BIOM621/LineardepCorrOrthogonal.pdf)
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 - [List of Machine Learning Concepts](https://en.wikipedia.org/wiki/List_of_machine_learning_concepts)
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 - [Slides on Several Machine Learning Topics](http://www.slideshare.net/pierluca.lanzi/presentations)
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 - [MIT Machine Learning Lecture Slides](http://www.ai.mit.edu/courses/6.867-f04/lectures.html)
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 - [Comparison Supervised Learning Algorithms](http://www.dataschool.io/comparing-supervised-learning-algorithms/)
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 - [Learning Data Science Fundamentals](http://www.dataschool.io/learning-data-science-fundamentals/)
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 - [Machine Learning mistakes to avoid](https://medium.com/@nomadic_mind/new-to-machine-learning-avoid-these-three-mistakes-73258b3848a4#.lih061l3l)
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 - [Statistical Machine Learning Course](http://www.stat.cmu.edu/~larry/=sml/)
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 - [TheAnalyticsEdge edX Notes and Codes](https://github.com/pedrosan/TheAnalyticsEdge)
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 - [In-depth introduction to machine learning in 15 hours of expert videos](http://www.dataschool.io/15-hours-of-expert-machine-learning-videos/)
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 - [Have Fun With Machine Learning](https://github.com/humphd/have-fun-with-machine-learning)
 
 <a name="interview" />