# Machine Deep Learning for Biology with Python and Tensorflow

Machine Deep Learning for Biology with Python and Tensorflow

*TensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today. The DeepLearning.AI TensorFlow Developer Professional Certificate program teaches you applied machine learning skills with TensorFlow so you can build and train powerful models.*

What you'll learn

- Build artificial neural networks with Tensorflow
- Classify images, data, and sentiments using deep learning
- Learn how to solve real life problem using the Machine learning techniques
- Understanding of basics of statistics and concepts of Machine Learning

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Description

Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you need. Data Scientists enjoy one of the top-paying jobs, with an average salary of $120,000 according to Glassdoor and Indeed. That's just the average! And it's not just about money - it's interesting work too!

If you've got some programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning practitioners in the tech industry - and prepare you for a move into this hot career path. This comprehensive machine learning tutorial. Most topics include hands-on Python code examples you can use for reference and for practice.

Each concept is introduced in plain English, avoiding confusing mathematical notation and jargon. It’s then demonstrated using Python code you can experiment with and build upon, along with notes you can keep for future reference. You won't find academic, deeply mathematical coverage of these algorithms in this course - the focus is on practical understanding and application of them. At the end, you'll be given a final project to apply what you've learned!

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.

It is used by major companies all over the world, including Airbnb, Ebay, Dropbox, Snapchat, Twitter, Uber, SAP, Qualcomm, IBM, Intel, and of course, Google!

Views Bestseller -- > Deep Learning Prerequisites: Linear Regression in Python

Deep Learning Prerequisites

- Programming. Programming is the fundamental requirement of deep learning. ...
- Statistics. Statistics refer to the study of using data and its visualization. ...
- Calculus. Calculus forms the basis for many machine learning algorithms. ...
- Linear Algebra. ...
- Probability. ...
- Data Science. ...
- Work on Projects.

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