Data Science 101 - Machine Lea

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About this app

Data Science 101 is an educational app to learn machine learning algorithms. Due to data science and artificial intelligence, new technologies are emerging and there is need for more specialization in this field.

This app is a beginner guide for anyone who wants to study data science and make their own machine learning models.
This app provides high quality resources for students to study data science and machine learning algorithms and also provides required code.

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Features:
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1. Learn various machine learning algorithms:
a. Linear Regression
b. k-means Clustering
c. KNN
d. SVM
e. Naive Bayes
f. Decision Trees

2. Includes code for developing models of various machine learning algorithms in Python.
Different datasets are used to develop models so that students can understand which algorithms to use.

3. Learn to develop various data science projects. Various projects are included in the application so that students can relate concepts with real life problems.
Some projects include:
a. Sentiment analysis
b. Web Scraping
c. Handwritten digit recognition

4. Learn various scientific libraries(Numpy, Pandas, Matplotlib).

There are many references available if students wants to study some concepts deeply.

Download this app and start learning for free.
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Ratings and reviews

I can give u one suggestion.. otherwise this app is wonderful like if we need to revise in short time this app is very helpful for that. And the suggestion is u can place that left and right Arrow navigation button at the end of the page...like it appears at the very beginning of the page.. and if have completed reading a page then we have to come top of the page again and then we navigate between the pages..but if u put that at bottom of the page then it will be more easy to navigate.

i seldom write reviews(almost never) but i really love this app and how briefly it encapsulates all the important theory of data science with right on point examples ! ads are annoying but you the app is free so thats okay.