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Tensorflow and Keras For Neural Networks and Deep Learning (Udemy.com)

Master the Most Important Deep Learning Frameworks (Tensorflow & Keras) for Python Data Science

Created by: Minerva Singh

Last updated October 2024

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What you will learn

  • 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 & Keras
  • Implement Deep Learning Based Unsupervised Learning With Tensorflow and Keras
  • Implement Deep Learning Based Supervised Learning With Tensorflow & Keras
  • Implement Convolution Neural Networks With Tensorflow & Keras

How it compares

Against the other 126 rated Udemy courses in Deep Learning on CourseDuck:

  • Rating4.4 out of 5higher than 32% of them
  • Reviews546#64 of 127 by number of reviews
  • Length8 hoursshorter than 57% of them
  • Last updatedOctober 2024more recently than 51% of them

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Course Description

THIS IS A COMPLETE NEURAL NETWORKS & DEEP LEARNING TRAINING WITH TENSORFLOW & KERAS IN PYTHON!

It is a full 7-Hour Python Tensorflow & Keras Neural Network & Deep Learning Boot Camp that will help you learn basic machine learning, neural networks and deep learning  using two of the most important Deep Learning frameworks- Tensorflow and Keras.                         

HERE IS WHY YOU SHOULD ENROLL IN THIS COURSE:

This course is your complete guide to practical machine & deep learning using the Tensorflow & Keras framework in Python..

This means, this course covers the important aspects of Keras and 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 and 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 Tensorflow and Keras is revolutionizing Deep Learning...

By gaining proficiency in Keras and 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 KERAS & 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 & Keras and give you a one-of-a-kind grounding in these frameworks!

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 & 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 Tensorflow syntax and graphing environment
• The basics of the Keras syntax
• Machine Learning, Supervised Learning, Unsupervised Learning in the Tensorflow & Keras frameworks
• You’ll even discover how to create artificial neural networks and deep learning structures with Tensorflow & Keras

BUT,  WAIT! THIS ISN'T JUST ANY OTHER DATA SCIENCE COURSE:

You’ll start by absorbing the most valuable Python Tensorflow and 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 Tensorflow and 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 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!

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Instructor Details

Minerva Singh

I completed a PhD (University of Cambridge, UK) in 2017 where I focussed on implementing data science techniques for quantifying the impact of forest loss on tropical ecosystems. I hold an MPhil (School of Geography and Environment) and an MSc (Department of Engineering) from Oxford University. I have more than 10 year's experience in conducting academic research (published in high level peer-reviewed international scientific journals such as PLOS One) and advising both non-governmental and industry stakeholders in data science, deep learning and earth observation (EO) related topics.

I have a strong track record in implementing machine learning, data visualization, spatial data analysis, deep learning and natural language processing tasks using both R and Python. In addition to being educated at the best universities in the world, I have honed my statistical and data analysis skills through many MOOCs, including The Analytics Edge (R based statistics and machine learning course offered by EdX), Statistical Learning (R-based Machine Learning course offered by Stanford online) and the IBM Data Science Professional certificate Track. I specialise in a variety of topics ranging from deep learning (Tensorflow, Keras) to machine learning to spatial data analysis (including EO data processing), data visualizations, natural language processing, financial analysis among others. I have acted as a peer reviewer on highly

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Reviews

4.4

546 ratings on Udemy

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By Raveena Sarkar on 11/15/2021

The course contains valuable and important information about the subject.. I am sure the quality of my work will enhance several notches with the adoption of this concept. The instructor has brilliantly explained the details of this concept in her lectures. She has total command over the subject.

By Ravi Srivastava on 11/10/2021

The course contains brilliant elucidation of the deep learning tools in Python data science. The course has immense potential for practical applications. The instructor has a knack of making the lecture so interesting that there is continuous engagement throughout the session.

By Raj Kumar Majumdar on 8/24/2021

The course contains important tools for deep learning. The concepts has vast opportunities for practical applications. The instructor is well-versed with finer details of the concept and her delivery is forceful and unambiguous.

By Rishilal Yadav on 8/6/2021

Tensorflow and keras are important tools, the utility of which has been brilliantly explained by the instructor in the course. She has a deep knowledge of the subject and her delivery is forceful. I find the course most relevant and useful for my work.

By Rajesh Kumar on 7/1/2021

It is an amazing course. Hands-on for me. the course has vast potential for practical applicability. The instructor is thorough about the subject and has a knack of keeping the students interested and engrossed during the lectures.

By Rinki Gupta on 5/3/2020

Half of the course is on Machine Learning, although the title was TensorFlow and Keras for NN and Deep Learning. However, Neural Network and Deep Learning only begin after half of the course is over. I wanted to learn use of TensorFlow and Keras for NN and Deep Learning. Some videos, 55-56 etc are blurred. The explanation is incorrect. The instructor says that CNN is only used for image classification. However, CNN can be used for time-series classification as well.

By Rumana Islam on 2/16/2020

This course helped me to understand how TensorFlow can be used to build the neural networks. It is a piece of art. I see how carefully and precise course was build and recorded. Thank you for awesome experience!

By Neamul Ishak on 12/11/2019

After finishing the course, It feels I am an expert in Neural network and DL. In lectures, all the topics are explained in details. All the documents are extremely helpful. Found exactly what I was looking for!

By Rafael Nogales on 5/10/2019

De momento lo unico que han hecho es explicar la sintaxis de numpy, esto debería darse por sabido en un curso de deep learning.. Además el profesor tampoco la domina (debería haber explicado por qué hay que meter una tupla a la matriz de ceros...) Se nota que se lo sabe pero va demasiado a la sintaxis y muy poco al concepto. o sea, si ya sabes otro framework de deep learning te puede valer. Si eres un experto en la materia a nivel teorico (como probablemente sea el caso de la profesora) te puede valer. Pero si quieres aprender deep learning sin saber a priori no te vale porque se centra sobre todo en la sintaxis y en hacer un montón de ejemplos. A mi personamente no me gustan los cursos que son 100% ejemplos, me gusta más un 30% teoria 70% ejemplos porque si no al final te pierdes. Aun así le voy a dar 3 estrellas y no considero que el dinero que me ha costado el curso esté malgastado porque aprendes cosas y crear el curso requiere mucho esfuerzo por parte del instructor y eso hay que apreciarlo.

By Susan Tang on 11/21/2018

I like the fact the teacher took us in hand and started with the basics of tensorflow and keras for DL. It makes the pace slow but I can see it is useful for beginners. It is very hands-on especially if you know Python

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Overall Score : 88 / 100