Machine Learning Practical Workout | 8 Real-World Projects
What you'll learn
- Deep Learning Practical Applications
- Machine Learning Practical Applications
- How to use ARTIFICIAL NEURAL NETWORKS to predict car sales
- How to use DEEP NEURAL NETWORKS for image classification
- How to use LE-NET DEEP NETWORK to classify Traffic Signs
- How to apply TRANSFER LEARNING for CNN image classification
- How to use PROPHET TIME SERIES to predict crime
- How to use PROPHET TIME SERIES to predict market conditions
- How to develop NATURAL LANGUAGE PROCESSING MODEL to analyze Reviews
- How to apply NATURAL LANGUAGE PROCESSING to develop spam filder
- How to use USER-BASED COLLABORATIVE FILTERING to develop recommender system
Course content
INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]9 lectures • 44min
- Welcome MessagePreview02:43
- Updates on Udemy Reviews01:04
- Course overviewPreview08:35
- BONUS: Learning Path00:33
- ML vs. DL vs. AIPreview16:15
- ML Deep Dive13:22
- Download Course Materials00:04
- BONUS: ML vs DL vs AI00:26
- BONUS: 5 Benefits of Jupyter Notebook00:59
ANACONDA AND JUPYTER INSTALLATION4 lectures • 18min
PROJECT #1: ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION12 lectures • 2hr 3min
PROJECT #2: DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION14 lectures • 2hr 46min
PROJECT #3: PROPHET TIME SERIES - CHICAGO CRIME RATE6 lectures • 59min
PROJECT #4: PROPHET TIME SERIES - AVOCADO MARKET6 lectures • 45min
PROJECT #5: LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION7 lectures • 1hr 33min
PROJECT #6: NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER9 lectures • 1hr 27min
PROJECT #7: NATURAL LANGUAGE PROCESSING - YELP REVIEWS15 lectures • 2hr 15min
PROJECT #8: USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM7 lectures • 1hr 23min
Requirements
- Deep Learning and Machine Learning basics
- PC with Internet connetion
Description
"Deep Learning and Machine Learning are one of the hottest tech fields to be in right now! The field is exploding with opportunities and career prospects. Machine/Deep Learning techniques are widely used in several sectors nowadays such as banking, healthcare, transportation and technology.
Machine learning is the study of algorithms that teach computers to learn from experience. Through experience (i.e.: more training data), computers can continuously improve their performance. Deep Learning is a subset of Machine learning that utilizes multi-layer Artificial Neural Networks. Deep Learning is inspired by the human brain and mimics the operation of biological neurons. A hierarchical, deep artificial neural network is formed by connecting multiple artificial neurons in a layered fashion. The more hidden layers added to the network, the more “deep” the network will be, the more complex nonlinear relationships that can be modeled. Deep learning is widely used in self-driving cars, face and speech recognition, and healthcare applications.
The purpose of this course is to provide students with knowledge of key aspects of deep and machine learning techniques in a practical, easy and fun way. The course provides students with practical hands-on experience in training deep and machine learning models using real-world dataset. This course covers several technique in a practical manner, the projects include but not limited to:
(1) Train Deep Learning techniques to perform image classification tasks.
(2) Develop prediction models to forecast future events such as future commodity prices using state of the art Facebook Prophet Time series.
(3) Develop Natural Language Processing Models to analyze customer reviews and identify spam/ham messages.
(4) Develop recommender systems such as Amazon and Netflix movie recommender systems.
The course is targeted towards students wanting to gain a fundamental understanding of Deep and machine learning models. Basic knowledge of programming is recommended. However, these topics will be extensively covered during early course lectures; therefore, the course has no prerequisites, and is open to any student with basic programming knowledge. Students who enroll in this course will master deep and machine learning models and can directly apply these skills to solve real world challenging problems."
Who this course is for:
- Data Scientists who want to apply their knowledge on Real World Case Studies
- Deep Learning practitioners who want to get more Practical Assigmetns
- Machine Learning Enthusiasts who look to add more projects to their Portfolio
Featured review
![Jared Rentz](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
Instructors
- 4.4 Instructor Rating
- 11,690 Reviews
- 103,000 Students
- 24 Courses
Ryan Ahmed is a best-selling Udemy instructor who is passionate about education and technology. Ryan's mission is to make quality education accessible and affordable to everyone. Ryan holds a Ph.D. degree in Mechanical Engineering from McMaster* University, with focus on Mechatronics and Electric Vehicle (EV) control. He also received a Master’s of Applied Science degree from McMaster, with focus on Artificial Intelligence (AI) and fault detection and an MBA in Finance from the DeGroote School of Business.
Ryan held several engineering positions at Fortune 500 companies globally such as Samsung America and Fiat-Chrysler Automobiles (FCA) Canada. Ryan has taught several courses on Science, Technology, Engineering and Mathematics to over 100,000+ students globally. He has over 15 published journal and conference research papers on state estimation, AI, Machine learning, battery modeling and EV controls. He is the co-recipient of the best paper award at the IEEE Transportation Electrification Conference and Expo (iTEC 2012) in Detroit, MI, USA.
Ryan is a Stanford Certified Project Manager (SCPM), certified Professional Engineer (P.Eng.) in Ontario, a member of the Society of Automotive Engineers (SAE), and a member of the Institute of Electrical and Electronics Engineers (IEEE). He is also the program Co-Chair at the 2017 IEEE Transportation and Electrification Conference (iTEC’17) in Chicago, IL, USA.
* McMaster University is one of only four Canadian universities consistently ranked in the top 100 in the world.
- 4.5 Instructor Rating
- 451,882 Reviews
- 1,496,234 Students
- 118 Courses
My name is Kirill Eremenko and I am super-psyched that you are reading this!
Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes.
From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events.
To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!
- 4.5 Instructor Rating
- 239,450 Reviews
- 1,071,766 Students
- 80 Courses
Hadelin is the co-founder and CEO at BlueLife AI, which leverages the power of cutting edge Artificial Intelligence to empower businesses to make massive profits by innovating, automating processes and maximizing efficiency. Hadelin is also an online entrepreneur who has created 70+ top-rated educational e-courses to the world on topics such as Machine Learning, Deep Learning, Artificial Intelligence and Blockchain, which have reached 1M+ students in 210 countries.
- 4.5 Instructor Rating
- 416,355 Reviews
- 1,411,661 Students
- 103 Courses
Hi there,
We are the SuperDataScience Social team. You will be hearing from us when new SDS courses are released, when we publish new podcasts, blogs, share cheatsheets and more!
We are here to help you stay on the cutting edge of Data Science and Technology.
See you in class,
Sincerely,
The Real People at SuperDataScience
- 4.4 Instructor Rating
- 14,551 Reviews
- 251,153 Students
- 41 Courses
Mitch is a Canadian filmmaker from Harrow Ontario, Canada. In 2016 he graduated from Dakota State University with a B.S, in Computer Graphics specializing in Film and Cinematic Arts.
Currently, Mitch operates as the Chairman of Red Cape Studios, Inc. where he continues his passion for filmmaking. He is also the Host of Red Cape Learning and Produces / Directs content for Red Cape Films.
He has reached over 250,000 + Students on Udemy and Produced more than 3X Best-Selling Courses.
Mitch is currently working Producing Online Educational Courses thru Red Cape Studios Inc.
Winning several awards at Dakota State University such as "1st Place BeadleMania", "Winner College 10th Anniversary Dordt Film Festival" as well as "Outstanding Artist Award College of Arts and Sciences".
Mitch has been Featured on CBC's "Windsors Shorts" Tv Show and was also the Producer/Director for TEDX Windsor, featuring speakers from across the Country.