Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (2023)

Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (1)


Category:Deep Learning


Buy for 189.99$

Course description

Data scientists, machine learning engineers, and AI researchers all have their own skillsets. But what is that one special thing they have in common?They are all masters of deep learning. We often hear about AI, or self-driving cars, or the 'algorithmic magic' at Google, Facebook, and Amazon. But it is not magic - it is deep learning. And more specifically, it is usually deep neural networks - the one algorithm to rule them all. Cool, that sounds like a really important skill; how do I become a Master of Deep Learning?There are two routes you can take: The unguided route - This route will get you where you want to go, eventually, but expect to get lost a few times. If you are looking at this course you've maybe been there. The 365 route - Consider our route as the guided tour. We will take you to all the places you need, using the paths only the most experienced tour guides know about. We have extra knowledge you won't get from reading those information boards and we give you this knowledge in fun and easy-to-digest methods to make sure it really sticks. Clearly, you can talk the talk, but can you walk the walk? - What exactly will I get out of this course that I can't get anywhere else?Good question! We know how interesting Deep Learning is and we love it! However, we know that the goal here is career progression, that's why our course is business focused and gives you real world practice on how to use Deep Learning to optimize business performance. We don't just scratch the surface either - It's not called 'Skin-Deep' Learning after all. We fully explain the theory from the mathematics behind the algorithms to the state-of-the-art initialization methods, plus so much more. Theory is no good without putting it into practice, is it? That's why we give you plenty of opportunities to put this theory to use. Implement cutting edge optimizations, get hands on with TensorFlow and even build your very own algorithm and put it through training! Wow, that's going to look great on your resume! Speaking of resumes, you also get a certificate upon completion which employers can verify that you have successfully finished a prestigious 365 Careers course - and one of our best at that! Now, I can see you're bragging a little, but I admit you have peaked my interest. What else does your course offer that will make my resume shine?Trust us, after this course you'll be able to fill your resume with skills and have plenty left over to show off at the interview. Of course, you'll get fully acquainted with Google' TensorFlow and NumPy, two tools essential for creating and understanding Deep Learning algorithms. Explore layers, their building blocks and activations - sigmoid, tanh, ReLu, softmax, etc. Understand the backpropagation process, intuitively and mathematically. You'll be able to spot and prevent overfitting - one of the biggest issues in machine and deep learningGet to know the state-of-the-art initialization methods. Don't know what initialization is? We explain that, tooLearn how to build deep neural networks using real data, implemented by real companies in the real world. TEMPLATES included! Also, I don't know if we've mentioned this, but you will have created your very own Deep Learning Algorithm after only 1 hour of the course. It's this hands-on experience that will really make your resume stand outThis all sounds great, but I am a little overwhelmed, I'm afraid I may not have enough experience. We admit, you will need at least a little understanding of Python programming but nothing to worry about. We start with the basics and take you step by step toward building your very first (or second, or third etc.) Deep Learning algorithm - we program everything in Python and explain each line of code. We do this early on and it will give you the confidence to carry on to the more complex topics we cover. All the sophisticated concepts we teach are explained intuitively. Our beautifully animated videos and step by step approach ensures the course is a fun and engaging experience for all levels. We want everyone to get the most out of our course, and the best way to do that is to keep our students motivated. So, we worked hard to ensure that students with varying skills are challenged without being overwhelmed. Each lecture builds upon the last and practical exercises mean that you can practice what you've learned before moving on to the next step. And of course, we are available to answer any queries you have. In fact, we aim to answer any and all question within 1 business day. We don't just chuck you in the pool then head to the bar and let you fend for yourself. Remember, we don't just want you to enrol - we want you to complete the course and become a Master of Deep Learning. OK, awesome! I feel much better about my level of experience now, but we haven't discussed yours! How do I know you can teach me to become a Master of Deep Learning?That's an understandable worry, but it's one we have no problem removing. We are 365 Careers and we've been creating online courses for ages. We have over 1,750,000 students and enjoy high ratings for all our Udemy courses. We are a team of experts who are all, at heart, teachers. We believe knowledge should be shared and not just through boring text books but in engaging and fun ways. We are well aware how difficult it is to build your knowledge and skills in the data science field, it's so new and has grown so fast that the education sector has struggled to keep up and offer any substantial methods of teaching these topic areas. We wanted to change things - to rock the boat - so we developed our unique teaching style, one that countless students have enjoyed and thrived with. And between us, we think this course is one of our favourites, so if this is your first time with us, you're in for a treat. If it's not and you've taken one of our courses before, then, you're still in for a treat! I've been hurt before though, how can I be sure you won't let me down?Easy, with Udemy's 30-day money back guarantee. We strive for the best and believe that our courses are the best out there. But you know what, everyone is different, and we understand that. So, we have no problem offering this guarantee, we want students who will complete and get the most out of this course. If you are one of the few who finds this course not what you wanted or expected then, get your money back. No questions, no risk, no problem. Great, that takes a load of my shoulders. What next?Click on the 'Buy now' button and take that first step toward a satisfying data science career and becoming a Master of Deep Learning.


Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (2)


We have 57985 courses

0 reviews

0 Rating

Udemy is one of the top online learning platforms founded in 2010 currently offering over 175,000 free and paid courses.

(Video) TensorFlow for Deep Learning course Udemy launch Q&A (live)

Related topics:

  • Matlab
  • Computer Vision
  • Big Data
  • Reinforcement Learning
  • PyTorch
  • Business Analytics
  • Apache Spark
  • Natural Language Processing
  • Statistics
  • Neural Networks
  • R
  • TensorFlow
  • Machine Learning
  • Data Science
  • Pandas
  • Tidyverse
  • Data Analysis
  • Keras
  • Python
  • Data Mining
  • Kaggle
  • Artificial Intelligence

Related courses

  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (3)

    The complete Machine Learning Data Science Course in Python


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (4)

    Introduction To Machine Learning with Python for beginners


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (5)

    Machine Learning: Data Analysis 2017


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (6)

    Machine Learning Algorithms in 7 Days


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (7)

    (Video) TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

    The Complete Neural Networks Bootcamp: Theory, Applications


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (8)

    Learn Web Application Development with Machine Learning


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (9)

    Machine Learning Practice Test

  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (10)

    Practical Deep Learning with Tensorflow 2.x and Keras


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (11)

    Machine Learning Made Easy: Beginner to Expert using Python


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (12)


    (Video) Tensorflow 2.0: Deep Learning and Artificial Intelligence

  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (13)

    Deep Reinforcement Learning using python


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (14)


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (15)

    ArcGIS: Learn Deep Learning in ArcGIS to advance GIS skills


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (16)

    AWS Certified Machine Learning - Specialty 2023


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (17)

    Theoretical Machine Learning From Scratch - Linear Models


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (18)


    (Video) Deep Learning Tutorial with Python | Machine Learning with Neural Networks [Top Udemy Instructor]
  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (19)

    Machine Learning for Flutter - The Complete 2023 Guide


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (20)

    Unsupervised Machine Learning: Cluster Analysis Algorithms


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (21)

    Professional Certificate in Data Engineering


  • Deep Learning with TensorFlow 2.0 | Course from Udemy | SkillCombo (22)

    Machine Learning for total Beginners


On our portal by searching online courses, you can take a course Deep Learning with TensorFlow 2.0 for a fee: 189.99. Selected course refers to category TensorFlow from a supplier Udemy, and would be a good choice for the difficulty level: any level of expertise. Experienced teacher gladly will help you in achieving new professional horizons. You can check out feedback of other users about this online course or share your thoughts to help other students make a decision

How to get new skills with Skillcombo?

Explore courses that align with your interests, dive into detailed descriptions, and browse through reviews to confidently choose your next learning path. Easily use our filters for level, duration, language, and price to find the right option for your goals.

(Video) Deep Learning with TensorFlow 2.0

  • 15+ popular course providers
  • 10000+ online courses in catalog
  • 1000+ IT subjects


Is TensorFlow 2.0 good? ›

TensorFlow 2.0 works efficiently with multi-dimensional arrays. It provides scalability of computation across machines and large data sets. TensorFlow 2.0 supports fast debugging and model building. It has a large community and provides TensorBoard to visualize the model.

How many days will it take to learn TensorFlow? ›

How Long Does it Take to Learn TensorFlow? If you already know Python programming and the theoretical foundations of neural networks, you can become a productive TensorFlow developer in 1 to 2 months. If you are a complete beginner in machine learning and programming, 3-6 months is a more realistic timeline.

Is learning TensorFlow difficult? ›

TensorFlow is considered both difficult to learn and use, largely due to the amount of programming skill needed. While TensorFlow is powerful and streamlines the development and training of machine learning models, the power that TensorFlow delivers requires extensive knowledge of how to use it.

Is TensorFlow good for deep learning? ›

TensorFlow was originally developed for large numerical computations without keeping deep learning in mind. However, it proved to be very useful for deep learning development as well, and therefore Google open-sourced it.

Is TensorFlow 2.0 better than PyTorch? ›

Performance: PyTorch 2.0 offers improved performance, making it faster and more efficient than its predecessor. However, TensorFlow still outperforms PyTorch 2.0 in terms of speed and memory efficiency. Ease of use: PyTorch is known for its ease of use and intuitive API, making it a popular choice among developers.

Is TensorFlow 2.0 same as Keras? ›

TensorFlow is an open-sourced end-to-end platform, a library for multiple machine learning tasks, while Keras is a high-level neural network library that runs on top of TensorFlow. Both provide high-level APIs used for easily building and training models, but Keras is more user-friendly because it's built-in Python.

Is it hard to pass TensorFlow exam? ›

It's impossible to pass the exam without true knowledge of TensorFlow and Deep Learning! In order to get Certified in TensorFlow, you have to: Pass a 5-hour test administered by Google and TensorFlow. Be deeply familiar (no pun intended) with all aspects of Deep Learning and advanced machine learning concepts.

Is TensorFlow easier than PyTorch? ›

In general, TensorFlow and PyTorch implementations show equal accuracy. However, the training time of TensorFlow is substantially higher, but the memory usage was lower. PyTorch allows quicker prototyping than TensorFlow, but TensorFlow may be a better option if custom features are needed in the neural network.

Is Google TensorFlow certification worth it? ›

The certificate is definitely worth getting to showcase your machine learning skills, especially if you're switching from another field. If you have some experience with machine learning (and deep learning), the course itself will act as a refresher module.

What is the disadvantage of TensorFlow? ›

1) Missing Symbolic loops: When we say about the variable-length sequence, the feature is more required.

Is TensorFlow losing popularity? ›

In contrast , both are powerful tools for deep learning. According to The Gradient's 2019 study of machine learning framework trends in deep learning projects, the two major frameworks continue to be TensorFlow and PyTorch, and TensorFlow is losing ground -- at least with academics.

Can a beginner learn TensorFlow? ›

TensorFlow makes it easy for beginners and experts to create machine learning models for desktop, mobile, web, and cloud.

Does anyone still use TensorFlow? ›

PyTorch and TensorFlow are far and away the two most popular Deep Learning frameworks today.

Should I use PyTorch or TensorFlow? ›

TensorFlow is good at deploying models in production to build AI products, while PyTorch is preferred in academia for research tasks. Thus, both TensorFlow and PyTorch are good frameworks to learn.

Which TensorFlow version is best? ›

Depends on your tf version, but should be 3.7–3.10.

Does Tesla use TensorFlow or PyTorch? ›

Tesla uses PyTorch for Autopilot, their self-driving technology. The company uses PyTorch to train networks to complete tasks for their computer vision applications, including object detection and depth modeling.

Is Google dropping TensorFlow? ›

With companies and researchers leaving Tensorflow and going to PyTorch, Google seems to be interested in moving its products to JAX, addressing some pain points from Tensorflow like the complexity of API, and complexity to train in custom chips like TPU.

Which Python version is best for TensorFlow 2? ›

Python version 3.4+ is considered the best to start with TensorFlow installation. Consider the following steps to install TensorFlow in Windows operating system.

Should I use TensorFlow 1 or 2? ›

(As per the TensorFlow team) It is important to understand that there is no battle of TensorFlow 1.0 vs TensorFlow 2.0 as TensorFlow 2.0 is the updated version and hence clearly better and smarter. It was built keeping in mind the drawbacks of TensorFlow 1.0 which was particularly hard to use and understand.

Is TensorFlow 2.0 backwards compatible? ›

Note that while the GraphDef version mechanism is separate from the TensorFlow version, backwards incompatible changes to the GraphDef format are still restricted by Semantic Versioning. This means functionality can only be removed or changed between MAJOR versions of TensorFlow (such as 1.7 to 2.0 ).

When did TensorFlow 2.0 come out? ›

Google released the updated version of TensorFlow, named TensorFlow 2.0, in September 2019.

What is the average salary of TensorFlow? ›

Employees who knows Tensorflow earn an average of ₹23.5lakhs, mostly ranging from ₹17.2lakhs to ₹52.1lakhs based on 136 profiles.

What is the passing score for TensorFlow exam? ›

Candidates are given five hours to complete the exam and must achieve a score of 90%. Those who do not pass may attempt the exam a total of three times in one year; the exam fee is required for each attempt.

How many people have TensorFlow certification? ›

— The TensorFlow Blog. July 12, 2021 — Posted by Alina Shinkarsky and Jocelyn Becker on behalf of the TensorFlow Team The TensorFlow Developer Certificate exam is celebrating its first anniversary with a big milestone: more than 3,000 people have passed the exam!

Does Disney use PyTorch? ›

We use a custom PyTorch IterableDataset that, in combination with PyTorch's DataLoader, allows us to read different parts of the video with parallel CPU workers. The video is split in chunks based on its I-frames and each worker reads different chunks.

Does DeepMind use TensorFlow or PyTorch? ›

The Google DeepMind AI project started out using Torch, and then switched to TensorFlow.

Is TensorFlow owned by Google? ›

TensorFlow is an open source framework developed by Google researchers to run machine learning, deep learning and other statistical and predictive analytics workloads.

How hard is the TensorFlow developer exam? ›

The exam is practical, you will work on regression, classification, Computer Vision, Natural Language Processing, and Time Series. Nothing too difficult, just enough to demonstrate proficiency in the framework and mindset. You will be graded on the quality of your models, that's all I can tell you.

How much does a Google TensorFlow developer earn? ›

Tensorflow Developer Salary. $94,000 is the 25th percentile. Salaries below this are outliers. $145,000 is the 75th percentile.

What is the most profitable Google certification? ›

The Google Data Analytics Professional Certificate is one of the most valuable Google career certifications you can get. Certified data analysts get an entry-level salary of $67,900 per year and can grow to more than $110K per year once they get 10+ years of working experience.

Is TensorFlow being replaced? ›

What pretty much everyone already knew was gonna happen, is now happening -- JAX is being gradually rolled out to replace TensorFlow (at least for internal use at Google). After losing out to PyTorch, Google is quietly moving to roll out a new AI framework internally called JAX.

Why not to use TensorFlow? ›

With Tensorflow, Google has created a framework that is simultaneously too low level to use comfortably for rapid prototyping, yet too high level to use comfortably in cutting edge research or in production environments that are resource constrained.

Do companies use TensorFlow? ›

Companies using Google TensorFlow for Machine Learning and Data Science Platform include: Anthem, Inc., a United States based Healthcare organisation with 83400 employees and revenues of $121.87 billion, Intel Corporation, a United States based Manufacturing organisation with 121100 employees and revenues of $63.10 ...

Does industry use TensorFlow or PyTorch? ›

Although TensorFlow has been widely recognized as the industry standard, offering an easy way to transition models from the development stage to deployment, PyTorch has made some recent strides with a new tool introduction. Let's take a look. Created by Google, it's one of the first serving tools to exist.

Does Uber use TensorFlow? ›

TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users.

Does TensorFlow have future? ›

Despite Google's significant investment in TensorFlow, the mistake of its design is so fundamental that it cannot be redone. Huang predicts that in the future, few people will still use TensorFlow, making this mistake one of the most costly Google has ever made in AI.

Do you need to know math for TensorFlow? ›

It is important to understand mathematical concepts needed for TensorFlow before creating the basic application in TensorFlow. Mathematics is considered as the heart of any machine learning algorithm. It is with the help of core concepts of Mathematics, a solution for specific machine learning algorithm is defined.

Should I start with Scikit learn or TensorFlow? ›

Scikit-learn and TensorFlow were designed to assist developers in creating and benchmarking new models, so their functional implementations are very similar, with the exception that Scikit-learn is used in practice with a broader range of models, whereas TensorFlow's implied use is for neural networks.

What should I learn before learning TensorFlow? ›

There are no prerequisites to learn TensorFlow. However, it is recommended that learners have a basic understanding of statistics, mathematics, and machine learning concepts.

When should I stop TensorFlow training? ›

Training will stop if the model doesn't show improvement over the baseline. Whether to restore model weights from the epoch with the best value of the monitored quantity. If False, the model weights obtained at the last step of training are used.

Is Jax better than TensorFlow? ›

Comparison with Other Frameworks

This can be useful for training neural networks because you don't have to write the code to compute the derivatives yourself. JAX is also more efficient than PyTorch and TensorFlow because it can automatically parallelize your code across multiple CPUs, GPUs or TPUs.

Is TensorFlow enough for machine learning? ›

TensorFlow is an end-to-end open source platform for machine learning. TensorFlow is a rich system for managing all aspects of a machine learning system; however, this class focuses on using a particular TensorFlow API to develop and train machine learning models.

Does Apple use PyTorch? ›

PyTorch, like Tensorflow, uses the Metal framework — Apple's Graphics and Compute API. PyTorch worked in conjunction with the Metal Engineering team to enable high-performance training on GPU. Internally, PyTorch uses Apple's Metal Performance Shaders (MPS) as a backend.

Does TensorFlow use NumPy? ›

TensorFlow implements a subset of the NumPy API, available as tf. experimental. numpy . This allows running NumPy code, accelerated by TensorFlow, while also allowing access to all of TensorFlow's APIs.

Does Google use PyTorch? ›

ML practitioners using PyTorch tell us that it can be challenging to advance their ML project past experimentation. This is why Google Cloud has built integrations with PyTorch that make it easier to train, deploy, and orchestrate models in production.

What GPU requirements for TensorFlow? ›

The following GPU-enabled devices are supported:
  • NVIDIA® GPU card with CUDA® architectures 3.5, 5.0, 6.0, 7.0, 7.5, 8.0 and higher. ...
  • For GPUs with unsupported CUDA® architectures, or to avoid JIT compilation from PTX, or to use different versions of the NVIDIA® libraries, see the Linux build from source guide.

Does TensorFlow 2.0 support GPU? ›

TensorFlow supports running computations on a variety of types of devices, including CPU and GPU.

What version of Python does TensorFlow 2.0 use? ›

TensorFlow is tested and supported on the following 64-bit systems: Python 3.8–3.11. Ubuntu 16.04 or later. Windows 7 or later (with C++ redistributable)

Is TensorFlow faster on CPU or GPU? ›

They noticed that the performance of TensorFlow depends significantly on the CPU for a small-size dataset. Also, they found it is more important to use a graphic processing unit (GPU) when training a large-size dataset.

How much faster is GPU than CPU for deep learning? ›

GPU vs CPU Performance in Deep Learning Models

Generally speaking, GPUs are 3X faster than CPUs.

Do you need Nvidia card for TensorFlow? ›

You can use AMD GPUs for machine/deep learning, but at the time of writing Nvidia's GPUs have much higher compatibility, and are just generally better integrated into tools like TensorFlow and PyTorch.

How do I install TensorFlow 2.0 in Python? ›

Step-by-step instructions
  1. System requirements. Ubuntu 16.04 or higher (64-bit) ...
  2. Install Miniconda. Miniconda is the recommended approach for installing TensorFlow with GPU support. ...
  3. Create a conda environment. ...
  4. GPU setup. ...
  5. Install TensorFlow. ...
  6. Verify install. ...
  7. System requirements. ...
  8. Check Python version.

Does Google use TensorFlow? ›

Tensorflow is used internally at Google to power all of its machine learning and AI.

How to install TensorFlow 2 with GPU? ›

Steps To Follow:
  1. Official Build From Source: The first step is to visit the official TensorFlow website to check out the latest version of TensorFlow that is currently available. ...
  2. Download Microsoft Visual Studio: ...
  3. Installing the CUDA toolkit: ...
  4. Installing CuDNN: ...
  5. Final command install:

How do I import TensorFlow 2.0 into Jupyter notebook? ›

How to Import Tensorflow in Jupyter Notebook
  1. Activate hello-tf conda environment.
  2. Open Jupyter.
  3. Import tensorflow.
  4. Delete Notebook.
  5. Close Jupyter.
Mar 25, 2023

Which NumPy version is compatible for TensorFlow 2.0 0? ›

0 as a dependency, but is compatible with NumPy<1.19. 0. NumPy in versions >=1.19.


1. Deep Learning A-Z: Hands-On Artificial Neural Networks Course in Python on Udemy - Full Review
(Greg Hogg)
2. TensorFlow & Keras Tutorial 2022 | Deep Learning With TensorFlow & Keras | Simplilearn
3. Deep Learning Tutorial with Python | Machine Learning with Neural Networks [Top Udemy Instructor]
4. Deep Learning with Keras and Tensorflow in Python and R
(Second Life 😁)
5. What is Machine Learning? (From Tensorflow 2.0)
(Lazy Programmer)
6. Machine Learning for Everybody – Full Course
Top Articles
Latest Posts
Article information

Author: Kelle Weber

Last Updated: 05/06/2023

Views: 5671

Rating: 4.2 / 5 (73 voted)

Reviews: 88% of readers found this page helpful

Author information

Name: Kelle Weber

Birthday: 2000-08-05

Address: 6796 Juan Square, Markfort, MN 58988

Phone: +8215934114615

Job: Hospitality Director

Hobby: tabletop games, Foreign language learning, Leather crafting, Horseback riding, Swimming, Knapping, Handball

Introduction: My name is Kelle Weber, I am a magnificent, enchanting, fair, joyous, light, determined, joyous person who loves writing and wants to share my knowledge and understanding with you.