Cryptocurrency-predicting RNN release that Intense Learning w/ Python, TensorFlow and Keras p.8

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.

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Python for Financial interpretation and stock market day trading – Udemy Review

Access the Python for financial analysis course here
Python is great for financial analysis and algorithmic stock market trading. In fact Wes McKinney developed Pandas, which is a python library, for a hedge fund group. Here I review the Udemy course by Jose Portilla. I am a big fan of his courses and have taken many of them, including this one. Watch the video to find out what I think.

More Python Learning resources:-

1. Complete Python Bootcamp

2. The Python Mega Course

3. Learning Python for Data Analysis and Visualization
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Time frame Number Study in Python | The right time Combination of Projecting | Data Skill with Python | Edureka

** Python Data Science Training : **
This Edureka Video on Time Series Analysis n Python will give you all the information you need to do Time Series Analysis and Forecasting in Python. Below are the topics covered in this tutorial:

1. Why Time Series?
2. What is Time Series?
3. Components of Time Series
4. When not to use Time Series
5. What is Stationarity?
6. ARIMA Model
7. Demo: Forecast Future

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About the Course

Edureka’s Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Python Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR.
During our Python Certification Training, our instructors will help you to:

1. Master the basic and advanced concepts of Python
2. Gain insight into the ‚Roles‘ played by a Machine Learning Engineer
3. Automate data analysis using python
4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application
5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn
6. Explain Time Series and it’s related concepts
7. Perform Text Mining and Sentimental analysis
8. Gain expertise to handle business in future, living the present
9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience

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Why learn Python?

Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations.
Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.
Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next „Big Thing“ and a must for Professionals in the Data Analytics domain.

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Call us at US: +18336900808 (Toll Free) or India: +918861301699

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Repeated Neural Networks like twitter (RNN / LSTM )by having Keras is that Python

Recurrent Neural Networks (RNN / LSTM )with Keras - Python

In this tutorial, we learn about Recurrent Neural Networks (LSTM and RNN). Recurrent neural Networks or RNNs have been very successful and popular in time series data predictions. There are several applications of RNN. It can be used for stock market predictions , weather predictions , word suggestions etc.

SimpleRNN , LSTM , GRU are some classes in keras which can be used to implement these RNNs. The backend can be Theano as well as TensorFlow.

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