What your going to learned:
- Reating Artificial Neural Networks with TensorFlow and Keras
- Deploy Machine Learning at scale with MLLIB from Apache Spark.
- Evaluate deep learning using images, data, and emotions.
- Make predictions using linear regression, multidimensional regression, and multivariate regression.
- Data visualization using MatPlotLib and Seaborn.
- Understand Empowerment Education - and how to make Pac-Man shoes.
- Data classification using K-mean clustering, Support Vector Machine (SVM), KNN, decision trees, naive Bayes and PCA.
- Use the Training/Test and Key folders to check your model and number three.
- Create a movie recommendation system with an easy-to-use, item-based collaborative filter.
- Clean the input data to get rid of emissions.
- Design and evaluation of A/B tests using t-tests and p-values.
needs
You need a desktop computer (Windows, Mac, or Linux) that can run Anaconda 3 or later. This course will guide you through the required free software installation process.
Requires some programming or scripting experience.
At least high school level math skills are required.
Description
New! Updated Production Module with Additional Content: Variable Auto Encoder (VAE) and Generative Reverse Model (GANs)
Machine learning and artificial intelligence (AI) are everywhere. If you want to know how companies, Google, Amazon, and even Udemy derive meaning and insight from big datasets, this data science course will give you the basics you need. According to Glassdoor and Indeed, data scientists have the highest paid jobs, with an average salary of $ 120,000. That's just average! And it's not just about money - it's an exciting business too!
If you have any programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning staff in the technology industry - and guide you through this hot career path. Will prepare This comprehensive machine learning tutorial includes over 100 to 15 hours of video lectures, and most of the topics include practical reading code samples that you can use for reference and training. I will use my 9 years of experience on Amazon and IMDb to guide you on what is important and what is not.
Each concept is presented in plain English, avoiding confusion with mathematical gestures and words. It will then be displayed with Python code so you can try and build, along with notes that you can keep for future reference. In this course you will not find any better religious and mathematical treatment of these algorithms - their practical understanding and application is emphasized. Finally, you will be given a graduate project to apply what you have learned!
The topics covered in this course are based on analyzing the real world needs of data scientists on job opportunities for data scientists. We cover machine learning, artificial intelligence and A-Z data mining techniques that real-time employees are looking for, including:
Deep Learning / Neural Networks with TensorFlow and Keras (MLPs, CNNs, RNNs)
Create artificial imagery using Variable AutoCoding (VAE) and Generator Generator Networks (GANs)
Map of data in Python with MatPlotLib and Seaborn
Learning transfer
Emotion analysis
Identify and classify images.
Regression analysis
K means clustering
Analysis of key components
Training / testing and certification
Bayesian Tips
Make decision trees and random
Numerous regressions.
Multi level models
Vector Machine Support:
Improving learning
Cooperative filters
Neighborhoods near K.
Prejudice / Conflict Trade
Learning team
Term frequency / reverse document frequency
Experimental design and A / B testing
Real Estate Technology
Adjust the hyper parameter.
... and much more! There is also a complete machine learning section with Apache Spark that extends these technologies to "big data" on analytics computer clusters.
If you're new to Python, don't worry - the course starts with a rough course. If you have already programmed something, you should pick it up soon. This course will show you how to configure your computer on Microsoft Windows PC, Linux Desktops and Max.
If you are a programmer who is looking for an exciting new career path, or a data analyst who wants to enter the technology industry, this course will be used by industry data scientists in the real world. Will teach the necessary technologies. General Chat Lounge These are topics that every successful technologist should know, so what are you waiting for? Register now!
"I started taking your courses ... I finally became interested and I never thought I would work for a company until a friend of mine offered me this job. Learned that learning at the academy is impossible and will be enjoyed immensely. For me, your course is the one that helped me to understand how to deal with business issues. How do I feel about it? I think you are one of the most inspiring teachers in machine learning, simple but charming. " - Kund Basu, Ph.D.
This course is for everyone:
Software developers or programmers looking for a lucrative career will learn a lot from this science of data science and machine learning.
Technology experts are curious as to how heavy learning really works.
Data analysts in the financial sector or other non-technical industries who are trying to enter the technology industry can use this course to learn.
Here is the download links
https://www.udemy.com/course/data-science-and-machine-learning-with-python-hands-on/
you can join over whats app group -> FREE COURSES 2022
