Sunday, February 18, 2018

Save list as CSV in ionic (PWA)

Read/Write file into devices

Installation (https://ionicframework.com/docs/native/file/)

Install the Cordova and Ionic Native plugins:
$ ionic cordova plugin add cordova-plugin-file
$ npm install --save @ionic-native/file
Add this plugin to your app's module

There are few ways you can use to download the file, but I'm using the easiest way, that is implementing the download which I'm not pretty sure if it runs ok on Android and iOS.
I'm not writing directly into the device storage as there are many things to consider such as storage area, security, etc.

Few references:

  1. http://ngcordova.com/docs/plugins/file/
  2. https://www.npmjs.com/package/cordova-plugin-file
  3. https://github.com/apache/cordova-plugin-file
  4. https://github.com/jiahao1553/demo-ionic2-save-csv/blob/master/src/pages/home/home.ts

List of Data Sciences and Machine Learning usefull link

Credit to: Shivam Panchal
As published by Shivam at Linked @ https://www.linkedin.com/pulse/data-science-machine-learning-beginners-path-shivam-panchal/

Platforms:

  1. What Is Hadoop? Hadoop Tutorial For Beginners https://youtu.be/n3qnsVFNEIU
  2. What is Apache Spark? The big data analytics platform explained http://www.techworld.com.au/article/629920/what-apache-spark-big-data-analytics-platform-explained/
  3. Apache Spark Tutorial: ML with PySpark https://www.datacamp.com/community/tutorials/apache-spark-tutorial-machine-learning
  4. A Beginner's Guide To Apache Pig https://hortonworks.com/tutorial/beginners-guide-to-apache-pig/
  5. Realtime Event Processing in Hadoop with NiFi, Kafka and Storm https://hortonworks.com/tutorial/realtime-event-processing-in-hadoop-with-nifi-kafka-and-storm/

Math:

  1. A Deep Dive Into Linear Algebra https://www.khanacademy.org/math/linear-algebra
  2. An Introduction to Combinatorics & Graph Theory https://www.whitman.edu/mathematics/cgt_online/cgt.pdf

Tools & Framework:

  1. TensorFlow Tutorial – Deep Learning Using TensorFlow https://youtu.be/yX8KuPZCAMo
  2. A 6-part introduction to the MXNet API https://becominghuman.ai/an-introduction-to-the-mxnet-api-part-1-848febdcf8ab
  3. Keras Tutorial: The Ultimate Beginner's Guide to Deep Learning in Python https://elitedatascience.com/keras-tutorial-deep-learning-in-python

Data Visualization:

  1. Building Python Data Apps with Blaze and Bokeh https://youtu.be/1gD9LMqREDs
  2. Matplotlib Tutorial: Python Plotting https://www.datacamp.com/community/tutorials/matplotlib-tutorial-python
  3. Python Bokeh Tutorial - Creating Interactive Web Visualizations https://youtu.be/Mz1AXUE0nR4

Concepts:

  1. Simple Linear Regression https://onlinecourses.science.psu.edu/stat501/node/250
  2. Simple and Multiple Linear Regression in Python https://medium.com/towards-data-science/simple-and-multiple-linear-regression-in-python-c928425168f9
  3. Linear Regression in R https://www.tutorialspoint.com/r/r_linear_regression.htm
  4. An Introduction To Logistic Regression http://ufldl.stanford.edu/tutorial/supervised/LogisticRegression/
  5. Building A Logistic Regression in Python, Step by Step by Susan Li https://medium.com/towards-data-science/building-a-logistic-regression-in-python-step-by-step-becd4d56c9c8
  6. Supervised and Unsupervised Machine Learning Algorithms https://machinelearningmastery.com/supervised-and-unsupervised-machine-learning-algorithms/
  7. 6 Easy Steps to Learn Naive Bayes Algorithm (with codes in Python and R) https://www.analyticsvidhya.com/blog/2017/09/naive-bayes-explained/
  8. A Tutorial on Support Vector Machines for Pattern Recognition http://www.cs.northwestern.edu/~pardo/courses/eecs349/readings/support_vector_machines4.pdf
  9. A Complete Tutorial on Tree Based Modeling from Scratch (in R & Python) https://www.analyticsvidhya.com/blog/2016/04/complete-tutorial-tree-based-modeling-scratch-in-python/

Python:

  1. A Complete Tutorial to Learn Data Science with Python from Scratch https://www.analyticsvidhya.com/blog/2016/01/complete-tutorial-learn-data-science-python-scratch-2/
  2. NumPy Tutorial: Data analysis with Python https://www.dataquest.io/blog/numpy-tutorial-python/
  3. Scipy Tutorial: Vectors and Arrays (Linear Algebra) https://www.datacamp.com/community/tutorials/python-scipy-tutorial
  4. Python Pandas Tutorial https://www.tutorialspoint.com/python_pandas/
  5. Machine Learning with scikit learn Part 1 & 2 https://youtu.be/2kT6QOVSgSghttps://youtu.be/WLYzSas511I

CS:

  1. A Thorough Overview of Computational Logic https://www.cs.utexas.edu/users/boyer/acl.pdf

Game Theory:

  1. Game Theory - A 3 Part Introduction https://youtu.be/x8gOi7D6QeQ

Statistics:

  1. Correlation & causality https://www.khanacademy.org/math/probability/scatterplots-a1/creating-interpreting-scatterplots/v/correlation-and-causality
  2. Analysis of variance (ANOVA) https://www.khanacademy.org/math/statistics-probability/analysis-of-variance-anova-library
  3. Understanding Hypothesis Tests: Significance Levels (Alpha) and P values in Statistics https://shar.es/1PANrc
  4. Characteristics of Good Sample Surveys and Comparative Studies https://onlinecourses.science.psu.edu/stat100/node/3
  5. Descriptive and Inferential Statistics https://www.thoughtco.com/differences-in-descriptive-and-inferential-statistics-3126224
  6. Intro to Probability Theory https://youtu.be/f9XFM8YLccg
  7. Introduction to Conditional Probability & Bayes theorem for data science https://www.analyticsvidhya.com/blog/2017/03/conditional-probability-bayes-theorem/
  8. Central limit theorem https://www.khanacademy.org/math/statistics-probability/sampling-distributions-library/sample-means/v/central-limit-theorem

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