Udemy free course, Full hands-on machine studying tutorial with knowledge science, Tensorflow, synthetic intelligence, and neural networks .

What you’ll study

  • Construct synthetic neural networks with Tensorflow and Keras
  • Classify photographs, knowledge, and sentiments utilizing deep studying
  • Make predictions utilizing linear regression, polynomial regression, and multivariate regression
  • Knowledge Visualization with MatPlotLib and Seaborn
  • Implement machine studying at huge scale with Apache Spark’s MLLib
  • Perceive reinforcement studying – and methods to construct a Pac-Man bot
  • Classify knowledge utilizing Ok-Means clustering, Help Vector Machines (SVM), KNN, Choice Timber, Naive Bayes, and PCA
  • Use prepare/take a look at and Ok-Fold cross validation to decide on and tune your fashions
  • Construct a film recommender system utilizing item-based and user-based collaborative filtering
  • Clear your enter knowledge to take away outliers
  • Design and consider A/B assessments utilizing T-Checks and P-Values

Necessities

  • You’ll want a desktop laptop (Home windows, Mac, or Linux) able to working Anaconda three or newer. The course will stroll you thru putting in the mandatory free software program.
  • Some prior coding or scripting expertise is required.
  • No less than highschool stage math abilities shall be required.

Description

New! Up to date for Winter 2019 with further content material on function engineering, regularization methods, and tuning neural networks – in addition to Tensorflow 2.0!

Machine Studying and synthetic intelligence (AI) is all over the place; if you wish to know the way firms like Google, Amazon, and even Udemy extract which means and insights from huge knowledge units, this knowledge science course gives you the basics you want. Knowledge Scientists take pleasure in one of many top-paying jobs, with a mean wage of $120,000 in accordance with Glassdoor and Certainly. That’s simply the common! And it’s not nearly cash – it’s fascinating work too!

In case you’ve acquired some programming or scripting expertise, this course will educate you the methods utilized by actual knowledge scientists and machine studying practitioners within the tech business – and put together you for a transfer into this scorching profession path. This complete machine studying tutorial consists of over 100 lectures spanning 14 hours of video, and most subjects embody hands-on Python code examples you should use for reference and for follow. I’ll draw on my 9 years of expertise at Amazon and IMDb to information you thru what issues, and what doesn’t.

Every idea is launched in plain English, avoiding complicated mathematical notation and jargon. It’s then demonstrated utilizing Python code you’ll be able to experiment with and construct upon, together with notes you’ll be able to hold for future reference. You gained’t discover tutorial, deeply mathematical protection of those algorithms on this course – the main target is on sensible understanding and software of them. On the finish, you’ll be given a remaining mission to use what you’ve discovered!

The subjects on this course come from an evaluation of actual necessities in knowledge scientist job listings from the most important tech employers. We’ll cowl the machine studying, AI, and knowledge mining methods actual employers are in search of, together with:

  • Deep Studying / Neural Networks (MLP’s, CNN’s, RNN’s) with TensorFlow and Keras
  • Knowledge Visualization in Python with MatPlotLib and Seaborn
  • Switch Studying
  • Sentiment evaluation
  • Picture recognition and classification
  • Regression evaluation
  • Ok-Means Clustering
  • Principal Part Evaluation
  • Practice/Check and cross validation
  • Bayesian Strategies
  • Choice Timber and Random Forests
  • A number of Regression
  • Multi-Degree Fashions
  • Help Vector Machines
  • Reinforcement Studying
  • Collaborative Filtering
  • Ok-Nearest Neighbor
  • Bias/Variance Tradeoff
  • Ensemble Studying
  • Time period Frequency / Inverse Doc Frequency
  • Experimental Design and A/B Checks
  • Function Engineering
  • Hyperparameter Tuning

…and rather more! There’s additionally a complete part on machine studying with Apache Spark, which helps you to scale up these methods to “large knowledge” analyzed on a computing cluster. And also you’ll additionally get entry to this course’s Fb Group, the place you’ll be able to keep in contact along with your classmates.

In case you’re new to Python, don’t fear – the course begins with a crash course. In case you’ve executed some programming earlier than, you need to decide it up rapidly. This course exhibits you methods to get arrange on Microsoft Home windows-based PC’s, Linux desktops, and Macs.

In case you’re a programmer seeking to swap into an thrilling new profession observe, or an information analyst seeking to make the transition into the tech business – this course will educate you the essential methods utilized by real-world business knowledge scientists. These are subjects any profitable technologist completely must learn about, so what are you ready for? Enroll now!

  • “I began doing all your course in 2015… Ultimately I acquired and by no means thought that I shall be working for company earlier than a pal provided me this job. I’m studying lots which was not possible to study in academia and having fun with it completely. To me, your course is the one which helped me perceive methods to work with company issues. How you can suppose to be a hit in company AI analysis. I discover you probably the most spectacular teacher in ML, easy but convincing.” – Kanad Basu, PhD

Who this course is for:

  • Software program builders or programmers who need to transition into the profitable knowledge science and machine studying profession path will study lots from this course.
  • Technologists inquisitive about how deep studying actually works
  • Knowledge analysts within the finance or different non-tech industries who need to transition into the tech business can use this course to learn to analyze knowledge utilizing code as a substitute of instruments. However, you’ll want some prior expertise in coding or scripting to achieve success.
  • When you’ve got no prior coding or scripting expertise, you need to NOT take this course – but. Go take an introductory Python course first.

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free udemy course, Machine Learning, Data Science and Deep Learning with Python
Measurement: 7.4GB. free udemy course, Machine Studying, Knowledge Science and Deep Studying with Python

SOURCE: https://www.udemy.com/course/data-science-and-machine-learning-with-python-hands-on/

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