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5 Real-Time Use Cases using Machine Learning
Learn Machine Learning and Deep Learning with 5 Real World projects
This Course Includes
udemy
4.4 (212 reviews )
4 total hours 
english
Online - Self Paced
course
Udemy
About 5 Real-Time Use Cases using Machine Learning
Are you ready to start your path to becoming a Data Scientist or ML Engineer?
This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!
Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!
This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!
This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! We will take you through 5 real-world projects and you can use those projects in your resume as well. The videos are designed in such a way that we will cover all the prerequisites and you just need to understand the flow.
We'll teach you how to create awesome Machine Learning and Deep Learning Projects with Python! Here a just a few of the topics we will be learning:
Programming with Python
NumPy with Python
Using pandas Data Frames to solve complex tasks
Use pandas to handle Excel Files
Use ML models from Scikit-learn
Use different NLP techniques
Make Neural Network Architecture
Moreover, the course is packed with quizzes that will help you check your knowledge while learning to build the projects.
And as a bonus, this course includes Python code templates which you can download and use as your own projects.
What You Will Learn?
- Learn how to program in Python using the latest Python 3.
- Learn to perform Classification and Regression modelling.
- Learn to use the popular library Scikit-learn in your projects.
- Real life case studies and projects to understand how things are done in the real world.
- Explore large datasets and wrangle data using Pandas.
- Build artificial neural networks with Tensorflow and Keras.
- Understand the intuition behind Artificial Neural Networks.
- Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0.
- Make robust Machine Learning models.
- How to improve your Machine Learning Models.
- Implement Machine Learning algorithms.