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The main objective of this problem is to forecast stock market data using traditional and advanced state of the art algorithms. EuroStockMarket Dataset contains the daily closing prices of major European stock indices: Germany DAX (Ibis), Switzerland SMI, France CAC, and UK FTSE. The data are sampled in business time, i.e., weekends and holidays are omitted. The stock market can have a huge impact on the people and the countries economy as a whole and hence predicting the prices of stock can reduce the risk of loss and maximize the profit.
To predict the stock price
The data is from the EU Stock market with the following columns with a time index.
2. Holt winter Method
3. ARIMA method
4. VAR method
5. Neural Network method
6. Finalise Model
7. Comparison and other potential approaches
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.
In this machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.
Hive Project -Learn to write a Hive program to find the first unique URL, given 'n' number of URL's.
In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.
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In this deep learning project, you will find similar images (lookalikes) using deep learning and locality sensitive hashing to find customers who are most likely to click on an ad.
In this deep learning project, you will build your own face recognition system in Python using OpenCV and FaceNet by extracting features from an image of a person's face.
Use the RACE dataset to extract a dominant topic from each document and perform LDA topic modeling in python.
In this PySpark project, you will simulate a complex real-world data pipeline based on messaging. This project is deployed using the following tech stack - NiFi, PySpark, Hive, HDFS, Kafka, Airflow, Tableau and AWS QuickSight.
In this Deep Learning Project on Image Segmentation Python, you will learn how to implement the Mask R-CNN model for early fire detection.