4.50 (197 reviews)
☑ Harness The Power Of Anaconda/iPython For Practical Data Science
☑ Learn How To Install & Use Tensorflow Within Anaconda
☑ Implement Statistical & Machine Learning With Tensorflow
☑ Implement Neural Network Modelling With Tensorflow
☑ Implement Deep Learning Based Unsupervised Learning With Tensorflow
☑ Implement Deep Learning Based Supervised Learning With Tensorflow
Complete Tensorflow Mastery For Machine Learning & Deep Learning in Python
THIS IS A COMPLETE DATA SCIENCE TRAINING WITH TENSORFLOW IN PYTHON!
It is a full 7-Hour Python Tensorflow Data Science Boot Camp that will help you learn statistical modelling, data visualization, machine learning and basic deep learning using the Tensorflow framework in Python..
HERE IS WHY YOU SHOULD ENROLL IN THIS COURSE:
This course is your complete guide to practical data science using the Tensorflow framework in Python..
This means, this course covers all the aspects of practical data science with Tensorflow (Google's powerful Deep Learning framework) and if you take this course, you can do away with taking other courses or buying books on Python Tensorflow 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 Tensorflow is revolutionizing Deep Learning...
By storing, filtering, managing, and manipulating data in Python and Tensorflow, 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 PYTHON TENSORFLOW 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 modeling features of Tensorflow and give you a one-of-a-kind grounding in Python based Tensorflow Data Science!
DISCOVER 8 COMPLETE SECTIONS ADDRESSING EVERY ASPECT OF PYTHON BASED TENSORFLOW 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 Tensorflow 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 Tensorflow syntax and graphing environment
• Statistical modelling with Tensorflow
• Machine Learning, Supervised Learning, Unsupervised Learning in the Tensorflow framework
• You’ll even discover how to create artificial neural networks and deep learning structures with Tensorflow
BUT, WAIT! THIS ISN'T JUST ANY OTHER DATA SCIENCE COURSE:
You’ll start by absorbing the most valuable Python Tensorflow Data Science 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 Tensorflow. 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 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, 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!
#tensorflow #python #deeplearning #android #java #neuralnetwork #models
INTRODUCTION TO TENSORFLOW : The Key Concepts and Software Tools
Welcome to the World of TensorFlow
Introduction to the Course
Data and Scripts For the Course
What is Artificial Intelligence?
Python Data Science Environment
For Mac Users
Introduction to IPython
IPython in Browser
Written Tensorflow Installation Instructions
Introduction to TensorFlow
A Brief Touchdown
A Brief Touchdown: Computational Graphs
Common Mathematical Operators in Tensorflow
A Tensorflow Session
Interactive Tensorflow Session
Constants and Variables in Tensorflow
Placeholders in Tensorflow
TensorBoard: Visualize Graphs in TensorFlow
Access TensorBoard Graphs
Other Python Packages and Their Interaction with Tensorflow
Miscellaneous Python Packages for Data Science
Introduction to Numpy
Create Numpy Arrays
Numpy for Statistical Operation
Introduction to Pandas
Read in Data from CSV
Read in Excel Data
Basic Data Cleaning
Convert to Tensor Objects
Statistical Modelling with Tensorflow
Linear Regression (From First Principles) With Tensorflow
Visualize the Results of OLS
Multiple Regression With Tensorflow-Part 1
Multiple Regression With Tensorflow-Machine Learning Approach
Estimate With Tensorflow Estimators
Multiple Regression With Tensorflow Estimators
More on Linear Regressor Estimator
GLM: Generalized Linear Model
Linear Classifier For Binary Classification
Accuracy Assessment For Binary Classification
Linear Classification with Binary Classification With Mixed Predictors
Introduction to Machine Learning
What is Machine Learning?
What is Unsupervised Learning?
Implement K-Means on Real Data
Random Forest (RF) for Binary Classification
Random Forest (RF) for Multiclass Classification
Artificial Neural Networks and Deep Learning with Tensorflow
Introduction to Artificial Neural Networks (ANN)
Multi Layer Perceptron (MLP)
Deep Neural Network (DNN) Classifier
Deep Neural Network (DNN) Classifier With Mixed Predictors
Deep Neural Network (DNN) Regression
Wide and Deep Learning
Autoencoders for Credit Card Fraud Detection
Autoencoders for Multiple Classes
Convolution Neural Network (CNN) For Image Analysis
Introduction to CNN
Implement a CNN for Multi-Class Supervised Classification
More on CNN
Pre-Requisite For Working With Imagery Data
CNN on Image Data
More on TFLearn
Autoencoders with CNN
Use Colabs for Jupyter Data Science
I certainly find the course very interesting. Actually I was looking for this kind of information which has been ideally arranged through these lectures.
Too broad and far reaching. Would have appreciated more in depth tensorflow course with less basic data science to begin with.
Course gives pretty good insight about deep learning. Very well organized session, lectures and lots of material ! Course is exactly what I hoped for!
Very straightforward and interesting course to learn about Tensorflow Deep Learning Data Science in Python from scratch. The tutorials were very informative. It's very helpful when instructor go through all the codes!
Fascinating and unique course. All the tough concepts were taught in a very simple way. The that this should be in the introductory course!
Leaned so much about deep learning! Explained in very simple and easy way! Resources and quiz are very informative! Thanks a lot!
Love it! Excellent sessions and lectures! Codes are impressive! Python is really great with Deep Learning!
Very detailed course. So many hands-on, practical and comprehensive resource for deep learning. Also includes lots of tips and tricks. Thanks a lot!
Perfect course for data science deep learning. You really make this course easy. Your python codes are such class!
They way you explain makes deep Learning concepts very intuitive and easily to understandable. Great job!
Conceptual and practical combination is delightful. excellent course session. Slow but qualitative for deep data science.
Lectures are scattered and unfocused, can't stand when someone reads directly off of slides, in one lecture about 10% of the screen was missing
The instructor is bad at communicating, and the video editing is very bad as well. It gets in the way of learning, which is unfortunate because if those things were better, the course would be a five star.
Trainer just goes through the concept with words instead of explaining how anything happens or how things are derived. Its almost like we have to just accept this step happens without knowing why
Great thought-out course content by an experienced teacher. I loved learning the like softmax, nonlinear activation functions, backpropagation, numpy vectorization. Minerva is interesting, and makes these subjects a lot of fun.