4.55 (41 reviews)
☑ Harness The Power Of Anaconda/iPython For Practical Data Science
☑ Learn How To Install & Use Tensorflow Within Anaconda
☑ Implement Neural Network Modelling With Keras
☑ Implement Deep Learning Based Unsupervised Learning With Keras
☑ Implement Deep Learning Based Supervised Learning With Keras
☑ Implement Convolution Neural Networks With Keras
THIS IS A COMPLETE NEURAL NETWORKS & DEEP LEARNING TRAINING WITH KERAS IN PYTHON!
It is a full 7-Hour Python Keras Neural Network & Deep Learning Boot Camp that will help you learn basic machine learning, neural networks and deep learning using one of the most important Deep Learning frameworks: Keras.
HERE IS WHY YOU SHOULD ENROLL IN THIS COURSE:
This course is your complete guide to practical machine & deep learning using the Keras framework in Python.
This means, this course covers the important aspects of Keras if you take this course, you can do away with taking other courses or buying books on Python Keras based data science.
In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal and advent of Keras is revolutionizing Deep Learning.
By gaining proficiency in Keras you can give your company a competitive edge and boost your career to the next level.
THIS IS MY PROMISE TO YOU: COMPLETE THIS ONE COURSE & BECOME A PRO IN PRACTICAL KERAS BASED DATA SCIENCE!
But first things first. My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment), graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).
I have several years of experience in analyzing real-life data from different sources using data science-related techniques and producing publications for international peer-reviewed journals.
Over the course of my research, I realized almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic and use data science interchangeably with machine learning..
This gives students an incomplete knowledge of the subject. My course, on the other hand, will give you a robust grounding in all aspects of data science within the Tensorflow framework.
Unlike other Python courses, we dig deep into the statistical modelling features of Tensorflow & Keras and give you a one-of-a-kind grounding in these frameworks!
DISCOVER 8 COMPLETE SECTIONS ADDRESSING EVERY ASPECT OF PYTHON BASED KERAS DATA SCIENCE:
• A full introduction to Python Data Science and powerful Python driven framework for data science, Anaconda
• Getting started with Jupyter notebooks for implementing data science techniques in Python
• A comprehensive presentation about Keras installation and a brief introduction to the other Python data science packages
• Brief introduction to the working of Pandas and Numpy
• The basics of the Keras syntax
• Machine Learning, Supervised Learning, Unsupervised Learning in the Keras frameworks
• You’ll even discover how to create artificial neural networks and deep learning structures with Keras
BUT, WAIT! THIS ISN'T JUST ANY OTHER DATA SCIENCE COURSE:
You’ll start by absorbing the most valuable Python Keras basics and techniques.
I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts.
My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement Python-based data science in real -life.
After taking this course, you’ll easily use packages like Numpy, Pandas, and Matplotlib to work with real data in Python along with gaining fluency in Keras. I will even introduce you to deep learning models such as Convolution Neural network (CNN) !!
The underlying motivation for the course is to ensure you can apply Python-based data science on real data into practice today, start analyzing data for your own projects whatever your skill level, and impress your potential employers with actual examples of your data science abilities.
This course will take students without a prior Python and/or statistics background from a basic level to performing some of the most common advanced data science techniques using the powerful Python-based Jupyter notebooks
It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to data science. However, the majority of the course will focus on implementing different techniques on real data and interpret the results..
After each video, you will learn a new concept or technique which you may apply to your own projects!
JOIN THE COURSE NOW!
Welcome To The Course
What is the Course About?
Data and Code Used in the Course
Why AI and Deep Learning?
Get Started With the Python Data Science Environment: Anaconda
Anaconda for Mac Users
The iPython Environment
Introduction to Python Data Science Packages
Python Packages for Data Science
Introduction to Numpy
Create Numpy Arrays
Numpy for Basic Vector Arithmetic
Numpy for Basic Matrix Arithmetic
Introduction to Pandas
Read in Data from CSV
Read in Data from Excel
Basic Data Cleaning
Introduction to Keras
What is Keras?
Keras Installation on Mac OS
Written Keras Installation Instructions
Some Basic Concepts
What is Machine Learning?
Neural Networks With Keras
Theory Behind ANN (Artificial Neural Network) and DNN (Deep Neural Networks)
Multi Layer Perceptron (MLP) With Keras
What is Backpropagation?
Keras MLP For Binary Classification
Accuracy Assessment For Binary Classification
Keras MLP for Multiclass Classification
Keras MLP for Regression
Unsupervised Learning With Keras
What is Unsupervised Learning?
Autoencoders for Unsupervised Classification
Autoencoders in Keras (Sparsity Constraints)
Autoencoders in Keras (Simple)
Deep Autoencoder With Keras
Deep Learning For Tensorflow & Keras
DNN Classifier With Keras
DNN Classifier With Keras-Example 2
Convolution Neural Network (CNN) For Image Analysis
Introduction to CNN
CNN Workflow for Keras
CNN With Keras
CNN on Image Data with Keras-Part 1
CNN on Image Data with Keras-Part 2
Autoencoders for With CNN- Keras
It is an amazing course as it contains finer details of very high quality of deep learning in Python . The concept has vast opportunities for practical use. The instructor has structured the course in an ideal way and her delivery generates interest in the lectures.
It is an amazing course which is beyond my expectations. I will be able to apply the concepts to my work and will greatly benefit out of it. The instructor is in total command of the finer points of the concepts of the course and her delivery is impressive.
The course is tailor-made for me. I see great opportunities of the concepts having practical usage. The instructor is thorough about the concepts and has an effective delivery method.
Complete Keras Bootcamp for deep learning in Python is a hands-on course for me . The instructor has beautifully arranged the lectures in the course and is very effective in driving home the point. I see great utility of this course in my work.
The contents as well as presentation of the course through lectures is of very high class. The delivery of the instructor is spell-binding. I see great utility of this course in my sphere of work.
very useful information is contained in the course which I will be able to apply for my work. Concepts are very clear to the instructor who keeps engaged through the lectures.
In the course are several videos impossible to watch because its quality, the content is accurate but could be better explained, some videos are just code reading
The course is extremely good. The lectures are crisp and to the point. Most of the concepts which I was working on got clarified. Enriching experience.
This course gave me a very good foundation of deep learning in python. It is a good starter to gain more experience on practical. Liked the way the instructor explained everything! Exercise and line by line code explanation was awesome! Loved it!
Exactly what I am looking for starting learning deep learning using keras. Practical examples with some good explanation made this course way to much simple and efficient.
Having issues obtaining the course material, archive appears corrupt. Attempting alternate methods to copy from Google - section 8 training data could be slowing down copy. Finally copied from google but not a code appears to be there. I see no notebooks, there are some text files that are renamed py files. Not all sections are in google??? I've type in what I can but some demo lectures are blurry (same in iPhone app).
Keras installation trouble shooting advice has not been provided but rest its an intense course on AI