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Machine Learning Data Science and Deep Learning with Python

Machine Learning Data Science and Deep Learning with Python

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Description
Machine Learning, Data Science and Deep Learning with Python

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













What you'll learn



• Build artificial neural networks with Tensorflow and Keras

• Classify images, data, and sentiments using deep learning

• Make predictions using linear regression, polynomial regression, and multivariate regression

• Data Visualization with MatPlotLib and Seaborn

• Implement machine learning at massive scale with Apache Spark's MLLib

• Understand reinforcement learning - and how to build a Pac-Man bot

• Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA

• Use train/test and K-Fold cross validation to choose and tune your models

• Build a movie recommender system using item-based and user-based collaborative filtering

• Clean your input data to remove outliers

• Design and evaluate A/B tests using T-Tests and P-Values



Requirements



• You'll need a desktop computer (Windows, Mac, or Linux) capable of running Anaconda 3 or newer. The course will walk you through installing the necessary free software.

• Some prior coding or scripting experience is required.

• At least high school level math skills will be required.



Description



New! Updated for Winter 2019 with extra content on feature engineering, regularization techniques, and tuning neural networks - as well as Tensorflow 2.0!

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 includes over 100 lectures spanning 14 hours of video, and most topics include hands-on Python code examples you can use for reference and for practice. I’ll draw on my 9 years of experience at Amazon and IMDb to guide you through what matters, and what doesn’t.

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. We'll cover the machine learning, AI, and data mining techniques real employers are looking for, including:

• Deep Learning / Neural Networks (MLP's, CNN's, RNN's) with TensorFlow and Keras

• Data Visualization in Python with MatPlotLib and Seaborn

• Transfer Learning

• Sentiment analysis

• Image recognition and classification

• Regression analysis

• K-Means Clustering

• Principal Component Analysis

• Train/Test and cross validation

• Bayesian Methods

• Decision Trees and Random Forests

• Multiple 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

• Feature Engineering

• Hyperparameter Tuning



...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.

If you're new to Python, don't worry - the course starts with a crash course. If you've done some programming before, you should pick it up quickly. This course shows you how to get set up on Microsoft Windows-based PC's, Linux desktops, and Macs.

If you’re a programmer looking to switch into an exciting new career track, or a data analyst looking to make the transition into the tech industry – this course will teach you the basic techniques used by real-world industry data scientists. These are topics any successful technologist absolutely needs to know about, so what are you waiting for? Enroll now!



• "I started doing your course in 2015... Eventually I got interested and never thought that I will be working for corporate before a friend offered me this job. I am learning a lot which was impossible to learn in academia and enjoying it thoroughly. To me, your course is the one that helped me understand how to work with corporate problems. How to think to be a success in corporate AI research. I find you the most impressive instructor in ML, simple yet convincing." - Kanad Basu, PhD



Who this course is for:



• Software developers or programmers who want to transition into the lucrative data science and machine learning career path will learn a lot from this course.

• Technologists curious about how deep learning really works

• Data analysts in the finance or other non-tech industries who want to transition into the tech industry can use this course to learn how to analyze data using code instead of tools. But, you'll need some prior experience in coding or scripting to be successful.

• If you have no prior coding or scripting experience, you should NOT take this course - yet. Go take an introductory Python course first.

File list
  • Machine Learning Data Science and Deep Learning with Python
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/1. Introduction.mp4 59.6 MB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/1. Introduction.vtt 4.2 KB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/2. Udemy 101 Getting the Most From This Course.mp4 19.8 MB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/2. Udemy 101 Getting the Most From This Course.vtt 3.6 KB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/3. [Activity] Getting What You Need.mp4 28.1 MB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/3. [Activity] Getting What You Need.vtt 4.2 KB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/3.1 Course Facebook Group.html 109 B
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/3.2 Course materials and setup steps.html 100 B
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/4. [Activity] Installing Enthought Canopy.mp4 109 MB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/4. [Activity] Installing Enthought Canopy.vtt 12.4 KB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/4.1 Enthought Canopy website.html 86 B
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/5. Python Basics, Part 1 [Optional].mp4 133.8 MB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/5. Python Basics, Part 1 [Optional].vtt 32.1 KB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/6. [Activity] Python Basics, Part 2 [Optional].mp4 77.2 MB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/6. [Activity] Python Basics, Part 2 [Optional].vtt 18.9 KB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/7. Running Python Scripts [Optional].mp4 44.7 MB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/7. Running Python Scripts [Optional].vtt 8.2 KB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/8. Introducing the Pandas Library [Optional].mp4 127.9 MB
  • Machine Learning, Data Science and Deep Learning with Python/1. Getting Started/8. Introducing the Pandas Library [Optional].vtt 15.7 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/1. Types of Data.mp4 77.2 MB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/1. Types of Data.vtt 14.7 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/10. [Exercise] Conditional Probability.mp4 130.4 MB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/10. [Exercise] Conditional Probability.mp4.jpg 104.3 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/10. [Exercise] Conditional Probability.txt 238 B
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/10. [Exercise] Conditional Probability.vtt 23.3 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/11. Exercise Solution Conditional Probability of Purchase by Age.mp4 28.7 MB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/11. Exercise Solution Conditional Probability of Purchase by Age.vtt 4.5 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/12. Bayes' Theorem.mp4 58.9 MB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/12. Bayes' Theorem.vtt 10.4 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/2. Mean, Median, Mode.mp4 56.1 MB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/2. Mean, Median, Mode.vtt 11.7 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/3. [Activity] Using mean, median, and mode in Python.mp4 92.7 MB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/3. [Activity] Using mean, median, and mode in Python.vtt 16.5 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/4. [Activity] Variation and Standard Deviation.mp4 110.8 MB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/4. [Activity] Variation and Standard Deviation.vtt 23.3 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/5. Probability Density Function; Probability Mass Function.mp4 30.1 MB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/5. Probability Density Function; Probability Mass Function.vtt 6.9 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/6. Common Data Distributions.mp4 75.4 MB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/6. Common Data Distributions.vtt 14.6 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/7. [Activity] Percentiles and Moments.mp4 114 MB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/7. [Activity] Percentiles and Moments.vtt 25.5 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/8. [Activity] A Crash Course in matplotlib.mp4 129.3 MB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/8. [Activity] A Crash Course in matplotlib.vtt 25.8 KB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/9. [Activity] Covariance and Correlation.mp4 116.7 MB
  • Machine Learning, Data Science and Deep Learning with Python/2. Statistics and Probability Refresher, and Python Practise/9. [Activity] Covariance and Correlation.vtt 23.4 KB
  • Machine Learning, Data Science and Deep Learning with Python/3. Predictive Models/1. [Activity] Linear Regression.mp4 100.5 MB
  • Machine Learning, Data Science and Deep Learning with Python/3. Predictive Models/1. [Activity] Linear Regression.vtt 23.1 KB
  • Machine Learning, Data Science and Deep Learning with Python/3. Predictive Models/2. [Activity] Polynomial Regression.mp4 66.8 MB
  • Machine Learning, Data Science and Deep Learning with Python/3. Predictive Models/2. [Activity] Polynomial Regression.vtt 15.9 KB
  • Machine Learning, Data Science and Deep Learning with Python/3. Predictive Models/3. [Activity] Multivariate Regression, and Predicting Car Prices.mp4 123.8 MB
  • Machine Learning, Data Science and Deep Learning with Python/3. Predictive Models/3. [Activity] Multivariate Regression, and Predicting Car Prices.vtt 22.6 KB
  • Machine Learning, Data Science and Deep Learning with Python/3. Predictive Models/4. Multi-Level Models.mp4 47.5 MB
  • Machine Learning, Data Science and Deep Learning with Python/3. Predictive Models/4. Multi-Level Models.vtt 9.7 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.mp4 98.6 MB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.vtt 18.9 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/10. [Activity] Decision Trees Predicting Hiring Decisions.mp4 95.9 MB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/10. [Activity] Decision Trees Predicting Hiring Decisions.vtt 20.3 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/11. Ensemble Learning.mp4 65.2 MB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/11. Ensemble Learning.vtt 13.1 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/12. Support Vector Machines (SVM) Overview.mp4 44.7 MB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/12. Support Vector Machines (SVM) Overview.vtt 9 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/13. [Activity] Using SVM to cluster people using scikit-learn.mp4 55 MB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/13. [Activity] Using SVM to cluster people using scikit-learn.vtt 10.8 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 58.1 MB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.vtt 11.9 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/3. Bayesian Methods Concepts.mp4 40.7 MB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/3. Bayesian Methods Concepts.vtt 8 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp4 89.1 MB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.vtt 15.8 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/5. K-Means Clustering.mp4 71.9 MB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/5. K-Means Clustering.vtt 15.6 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.mp4 57.3 MB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.vtt 10.5 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/7. Measuring Entropy.mp4 35 MB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/7. Measuring Entropy.vtt 6.3 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/8. [Activity] Install GraphViz.html 1.5 KB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/9. Decision Trees Concepts.mp4 86.5 MB
  • Machine Learning, Data Science and Deep Learning with Python/4. Machine Learning with Python/9. Decision Trees Concepts.vtt 19.1 KB
  • Machine Learning, Data Science and Deep Learning with Python/5. Recommender Systems/1. User-Based Collaborative Filtering.mp4 86.4 MB
  • Machine Learning, Data Science and Deep Learning with Python/5. Recommender Systems/1. User-Based Collaborative Filtering.vtt 17.5 KB
  • Machine Learning, Data Science and Deep Learning with Python/5. Recommender Systems/2. Item-Based Collaborative Filtering.mp4 75 MB
  • Machine Learning, Data Science and Deep Learning with Python/5. Recommender Systems/2. Item-Based Collaborative Filtering.vtt 18.1 KB
  • Machine Learning, Data Science and Deep Learning with Python/5. Recommender Systems/3. [Activity] Finding Movie Similarities.mp4 107.8 MB
  • Machine Learning, Data Science and Deep Learning with Python/5. Recommender Systems/3. [Activity] Finding Movie Similarities.vtt 18.2 KB
  • Machine Learning, Data Science and Deep Learning with Python/5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.mp4 94.9 MB
  • Machine Learning, Data Science and Deep Learning with Python/5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.vtt 15.2 KB
  • Machine Learning, Data Science and Deep Learning with Python/5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.mp4 132.6 MB
  • Machine Learning, Data Science and Deep Learning with Python/5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.vtt 20.5 KB
  • Machine Learning, Data Science and Deep Learning with Python/5. Recommender Systems/6. [Exercise] Improve the recommender's results.mp4 84.2 MB
  • Machine Learning, Data Science and Deep Learning with Python/5. Recommender Systems/6. [Exercise] Improve the recommender's results.vtt 12 KB
  • Machine Learning, Data Science and Deep Learning with Python/6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.mp4 40.3 MB
  • Machine Learning, Data Science and Deep Learning with Python/6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.vtt 8.1 KB
  • Machine Learning, Data Science and Deep Learning with Python/8. Apache Spark Machine Learning on Big Data/7. [Activity] Decision Trees in Spark.mp4 193.2 MB
  • Machine Learning, Data Science and Deep Learning with Python/ReadMe.txt 428 B

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