I wanted to learn to predict future events like......being able to predict number of plane crashes in 2018 using past two decades of plane crash data.....or.....predict how many tee-shirts with justin beibers face on it will be sold by 2018 depending upon fan base from previuos data..........or how many iphones 8's and samsungs s9's will be sold if they decide to launch on the same exact date....predicting somewhat accurate whole sale market.....stuff like that....please suggest a book...i really love head first series....is head first data analysis right for me? ....I dont lnow if i can ask questions other than programming here or not.....but here i am.....By the way does big data have anything to do with this?
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Questions asking us to recommend or find a **book** ... or other off-site resource are off-topic for Stack Overflow as they tend to attract opinionated answers and spam. – Vanity Slug - codidact.com Aug 21 '17 at 21:00
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dude, this question is awesome, one of my favorites now I think...but way too broad. Decompose it into like 5 separate questions. – Mark Giaconia Aug 21 '17 at 21:01
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A book for maschine learning might be interesting – Matthias H Aug 21 '17 at 21:02
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@MatthiasH there is [The Maschine Studio Cookbook](https://itunes.apple.com/us/book/the-maschine-studio-cookbook/id837089872?mt=11). I doubt it's relevant to predicting future purchases :) – Vanity Slug - codidact.com Aug 22 '17 at 14:23
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it all falls in the category of data science (which is big data and data analysis). What you need for predictions and such stuff is some machine learning approach to data you have or can access about stuff you want to predict.
I'd recommend this, newest series of articles: https://medium.com/machine-learning-for-humans/why-machine-learning-matters-6164faf1df12
Apart from really nice intro, you'll find lots of resources for further learning there.
Also I highly recommend deeplearning.ai and machine learning course from Stanford you can find on Coursera.
Cheers!
Rastko
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I think most of the scenarios that you have asked are a case of Supervised Learning which is a type of machine learning, wherein you have previous data to train your machine learning model with the input and output values and once you have trained a model you feed new input values and it gives you the output which is the prediction.
I would highly recommend the following Machine Learning course by Andrew NG which on Coursera which covers all the basics of ML including Supervised and Unsupervised Learning.
https://www.coursera.org/learn/machine-learning
As for the books the following link from Analytics Vidya is a great place to start with, you can go through the books as they can give you some good basics of statistics and data sciences.
As for the differences between Data Science, Data Analytics and Big Data. Data science and data analytics are similar in the sense that they both try to find patterns in data and based on those pattern you derive some insights.
Big data on the other hand is basically Data of huge size which is distributed across multiple machines, so you can store and compute large amount of data simultaneously and in parallel.
So you may ask how is big data and machine learning related? well the answer lies in the training of machine learning model, since the accuracy of prediction is to a certain extent depends on the amount of data you train it on. So more the training data better the predictions and in terms of quantity big data way ahead of others, hence the relation.
Ajay Sant
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