Hi there, we are James and Sajid. Both of us are working as data scientists for various banks here in London, and we have both gone a long way before arriving at our current position in the market.
Do you wish to become a data scientist and build yourself a strong portfolio? This course will allow you to develop your Python skills tutored by professionals. You will be able to add Natural Language Processing and Deep Learning to your CV and start getting paid for your skills.
In this course, you will learn how to apply the newest methods in machine learning and natural language processing to predictive analysis of the stock market and cryptocurrency.
Use the latest technologies available such as TensorFlow, PlotLy, HuggingFace’s Transformers, Flair, spaCy, and many of the essential classics like Pandas, RegEx, Numpy, and more!
We will cover:
– TensorFlow
– Sentiment Analysis
– Transformers (including Google AI’s BERT)
– APIs (including Twitter and Reddit)
– Trading for cryptocurrencies
– Named Entity Recognition (NER)
Take this course if you are learning Python and/or Machine Learning and looking to apply these skills to the stock market. We can’t promise to ‘fix’ on the stock market, but we can promise that you will learn many priceless skills that when applied correctly, can translate to a real benefit both in the job market, and the stock market.
The course is taught by two data scientists from the finance sector. Sajid of Trading 707, who works in Banking and Capital Markets. And James of Aurelio, who specializes in Natural Language Processing (NLP).
Who this course is for:
- Beginner Python developer
- Data scientist
- Finance and Computer Science student
Here’s What You’ll Get in 2021: Algorithmic Trading with Machine Learning in Python
– Download Sample files “2021: Algorithmic Trading with Machine Learning in Python”
Course Requirement: 2021: Algorithmic Trading with Machine Learning in Python
Real Value: $199
One time cost: USD 59
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What is the refund policy “2021: Algorithmic Trading with Machine Learning in Python”?
- We’ll Bear The Risk, You’ll Take The Results…
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