An introduction to the construction of a profitable machine learning strategy. Covers the basics of classification algorithms, data preprocessing, and feature selection. Discussion of Python machine learning resources; including the Sentdex channel, and the Python Machine learning book. In the next video we will look at different data sources and how to clean the data.
*** Sentdex Channel ***
*** Python Machine Learning – Sebastian Raschka ***
Here are some very useful websites if you would like to learn more about Neural Networks and Fuzzy Logic.
Learn Artificial Neural Networks is website dedicated to providing educational information about artificial intelligence technologies. They have two great articles explaining Neural Networks and Fuzzy Logic in details. There are also other articles related to AI.
In Akri Ltd, there is an article titled „From Logic to Fuzzy Logic“ which compares traditional logic and Fuzzy logic using real-world examples, showcasing how Fuzzy Logic has revolutionized the world.
Holos is an Europe-based company which provides its clients with products and services that improve the information access, support decisions and generate knowledge. In its company website, Holos explains how it integrates Fuzzy Logic into decision-making activities.
Here is an article explaining „A Fuzzy Logic based Trading System“
This article explains the importance of Neural Networks and Fuzzy Logic using diagrams to help understand.
http://www.cs.berkeley.edu/~zadeh/papers/Fuzzy%20Logic%2c%20Neural%20Networks%2c%20and%20Soft%20Computing-1994.pdf Video Rating: / 5
In this Python for Data Science Tutorial you will learn about Time series Visualization in python using matplotlib and seaborn in jupyter notebook (Anaconda).
This is the 10th Video of Python for Data Science Course! In This series I will explain to you Python and Data Science all the time! It is a deep rooted fact, Python is the best programming language for data analysis because of its libraries for manipulating, storing, and gaining understanding from data. Watch this video to learn about the language that make Python the data science powerhouse. Jupyter Notebooks have become very popular in the last few years, and for good reason. They allow you to create and share documents that contain live code, equations, visualizations and markdown text. This can all be run from directly in the browser. It is an essential tool to learn if you are getting started in Data Science, but will also have tons of benefits outside of that field. Harvard Business Review named data scientist „the sexiest job of the 21st century.“ Python pandas is a commonly-used tool in the industry to easily and professionally clean, analyze, and visualize data of varying sizes and types. We’ll learn how to use pandas, Scipy, Sci-kit learn and matplotlib tools to extract meaningful insights and recommendations from real-world datasets.
Download Link for Cars Data Set:
Download Link for Enrollment Forecast:
Download Link for Iris Data Set:
Download Link for Snow Inventory:
Download Link for Super Store Sales:
Download Link for States:
Download Link for Spam-base Data Base:
Download Link for Parsed Data:
Download Link for HTML File:
Quick simple tutorial on ARIMA time series forecasting in Python. Data : https://drive.google.com/open?id=1ytbaSkksPbdljdkzH4EjC1chGYkJuwZM
Code (jupyter) : https://drive.google.com/open?id=1Z-35uZpDfwVcPXlY-BrdvdnYczAbDkXI
Looking for Data Science Projects?
Your can work on above project ‚Time Series Forecasting Theory Part 2‘
Datamites is one of the leading institutes in Bangalore, Pune and Hyderabad for Data Science courses. You can learn Data Science with Machine Learning, Statistics, Python, Tableau etc,..
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Welcome to part 8 of the Deep Learning with Python, Keras, and Tensorflow series. In this tutorial, we’re going to work on using a recurrent neural network to predict against a time-series dataset, which is going to be cryptocurrency prices.
Text tutorials and sample code: https://pythonprogramming.net/cryptocurrency-recurrent-neural-network-deep-learning-python-tensorflow-keras/
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