Machine Learning, Data Science and Deep Learning with Python

Machine Learning, Data Science and Deep Learning with Python Course includes 16 hrs video content and enrolled by 169,368 students and received a 4.5 average review out of 5. Now, you will get 89%OFF on the original price of the course and discount price differs from country to country, and the course provider offers 30-days money-back guarantee! If you are not satisfied in any way, you’ll get your money back.

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

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
  • Creating synthetic images with Variational Auto-Encoders (VAE’s) and Generative Adversarial Networks (GAN’s)
  • 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

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.

Can I download Machine Learning, Data Science and Deep Learning with Python course?

You can download videos for offline viewing in the Android/iOS app. When course instructors enable the downloading feature for lectures of the course, then it can be downloaded for offline viewing on a desktop.
Can I get a certificate after completing the course?
Yes, upon successful completion of the course, learners will get the course e-Certification from the course provider. The Machine Learning, Data Science and Deep Learning with Python course certification is a proof that you completed and passed the course. You can download it, attach it to your resume, share it through social media.
Are there any other coupons available for this course?
You can check out for more Udemy coupons @ www.coursecouponclub.com
Note: 100% OFF Udemy coupon codes are valid for maximum 3 days only. Look for "ENROLL NOW" button at the end of the post.
Disclosure: This post may contain affiliate links and we may get small commission if you make a purchase. Read more about Affiliate disclosure here.
Deal Score0

Udemy Popular Instructors : Rob Percival | Phil Ebiner | 365 Careers | Chris Haroun | Colt Steele | Jose Portilla | Kirill Eremenko | Maximilian Schwarzmüller | Ben Tristem | Daragh Walsh | Evan Kimbrell | Dr. Angela Yu | Laurence Svekis | Start-Tech Academy | Mike Wheeler | Joeel & Natalie Rivera | Stephane Maarek | Hadelin de Ponteves | Tim Buchalka | Scott Duffy | Valentin Despa | Mohsen Hassan | Jaysen Batchelor | Jason Dion | KodeKloud Training | Stephen Grider | Daniel Walter Scott | Rahul Shetty | Andrei Neagoie | in28Minutes Official | Mauricio Rubio | Leila Gharani | Chris Croft | Lawrence M. Miller | Steve Ballinger | Eshant Garg | Juan Gabriel Gomila Salas | Alexander Hagmann | CADCIM Technologies | Sandeep Kumar ­ | Neil Cummings | Denis Panjuta | Tarek Roshdy | Minerva Singh | Matthew Barnett | Siva Prasad | Dr Karen E Wells | Graham Nicholls | Kain Ramsay |

Courses by Top Universities and Institutions: Google Cloud | Stanford University | Deeplearning.ai | University of Michigan | University of Illinois | IBM | Johns Hopkins University | Northwestern University | University of Minnesota | HSE University | Duke Univercity | New York Institute of Finance | Rice University | University of Washington | Yale University |
Course Coupon Club
Logo