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Machine Learning, Data Science and Deep Learning with Python

Complete hands-on machine learning tutorial with data science, Tensorflow, artificial intelligence, and neural networks

4.500 4.5 (13,214 ratings)

87,260 enrollments

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Description

Featured on: Mar 9, 2019

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!

The topics in this course come from an analysis of real requirements in data scientist job listings from the biggest tech employers. It’ll cover the machine learning and data mining techniques real employers are looking for, including:

  • Deep Learning / Neural Networks (MLP’s, CNN’s, RNN’s)
  • Regression analysis
  • K-Means Clustering
  • Principal Component Analysis
  • Train/Test and cross validation
  • Bayesian Methods
  • Decision Trees and Random Forests
  • Multivariate Regression
  • Multi-Level Models
  • Support Vector Machines
  • Reinforcement Learning
  • Collaborative Filtering
  • K-Nearest Neighbor
  • Bias/Variance Tradeoff
  • Ensemble Learning
  • Term Frequency / Inverse Document Frequency
  • Experimental Design and A/B Tests

…and much more. There’s also an entire section on machine learning with Apache Spark, which lets you scale up these techniques to “big data” analyzed on a computing cluster. And you’ll also get access to this course’s Facebook Group, where you can stay in touch with your classmates.

4.500 4.5

(13,214 ratings)

87,260 enrollments

Discount Offer