Machine Deep Learning for Biology with Python and Tensorflow
Complete hands-on machine learning tutorial with Python and Tensorflow
What you’ll learn
Machine Deep Learning for Biology with Python and Tensorflow
- Tensorflow allows you to create artificial neural networks.
- Deep learning can be used to classify images, data, and sentiments.
- Learn how to use machine learning techniques to tackle real-world challenges.
- Understanding of the fundamentals of statistics and machine learning ideas.
Requirements
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No prior experience is required.
Description
This data science course will teach you the principles of machine learning and artificial intelligence (AI), which are used by organizations like Google, Amazon, and even to extract meaning and insights from large data sets. According to Glassdoor and Indeed, data scientists have one of the highest-paying careers, with an average income of $120,000. That’s just the standard deviation! It’s not just about the money; it’s also about doing an interesting job!
This course will teach you the techniques used by professional data scientists and machine learning practitioners in the tech industry – and prepare you for a move into this hot career field if you have any programming or scripting experience. This comprehensive machine learning lesson will teach you all you need to know about machine learning. The majority of the topics offer practical Python code examples that you may use for reference and practice.
Machine Deep Learning for Biology with Python and Tensorflow
Each idea is explained in plain English, avoiding the use of jargon and complicated mathematical symbols. It’s then illustrated with Python code that you can play around with and develop on, as well as notes for future reference. This course does not focus on academic, thoroughly mathematical discussion of these algorithms; rather, it focuses on practical comprehension and application.
TensorFlow is an open source software framework that uses data flow graphs to do numerical computations. The graph’s nodes represent mathematical operations, while the graph’s edges represent the multidimensional data arrays (tensors) that are exchanged between them. With the flexible architecture, you may use a single API to deploy compute to one or more CPUs or GPUs in a desktop, server, or mobile device.
Airbnb, eBay, Dropbox, Snapchat, Twitter, Uber, SAP, Qualcomm, IBM, Intel, and, of course, Google is among the companies that utilize it.
Become an expert in machine learning right now! Inside the course, we’ll see you!
Who this course is for:
- Python students are keen to study the latest TensorFlow Deep Learning Techniques.
- This course will benefit software professionals or programmers who want to go into the lucrative field of data science and machine learning.
- This course is not for you if you have no prior coding or scripting knowledge. First, enroll in a Python beginner course.
- This course can be used by data analysts in finance or other non-tech businesses who wish to migrate into the tech industry to learn how to evaluate data using code rather than tools. However, you’ll need some prior coding or scripting skills to be effective.
Mathematical Foundations of Machine Learning
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