Get ready to pass the TensorFlow Developer Certificate Exam by Google and become an expert in AI, Machine Learning, and Deep Learning. Learn to build TensorFlow models for Computer Vision, Convolutional Neural Networks, and Natural Language Processing. Boost your skills and career opportunities in the Machine Learning industry with this comprehensive course. Join now and become a top paid TensorFlow developer!
Macintosh/Windows/Linux - all working frameworks work with this course!
No past TensorFlow information required. Essential comprehension of Machine Learning is useful
Just sent off with all cutting edge prescribed procedures for building neural networks with TensorFlow and breezing through the TensorFlow Developer Certificate test!
Join a live web-based local area of over 900,000+ understudies and a course shown by a TensorFlow certified master. This course will take you from outright amateur with TensorFlow, to making cutting edge deep learning neural networks and turning out to be important for Google's TensorFlow Confirmation Network.
TensorFlow specialists procure up to $204,000 USD a year, with the typical salary floating around $148,000 USD as per 2023 measurements. By passing this certificate, which is formally acknowledged by Google, you will join the developing Machine Learning industry and turning into a top paid TensorFlow developer! Assuming you breeze through the test, you will likewise be essential for Google's TensorFlow Developer Network where scouts can track down you.
The objective of this course is to help you every one of the abilities vital for you to proceed to breeze through this test and get your TensorFlow Confirmation from Google so you can show it on your resume, LinkedIn, Github and other web-based entertainment stages to really make you stick out.
Here is a full course breakdown of all that we will educate (indeed, it's actual extensive, yet don't be threatened, as we will show you all that without any preparation!):
This course will be exceptionally hands on and project based. You will not simply be gazing at us educate, yet you will really get to explore, do activities, and assemble machine learning models and projects to impersonate genuine situations. Above all, we will show you what the TensorFlow test will resemble for you. Toward the finish, all things considered, you will create ranges of abilities expected to foster current deep learning arrangements that huge tech organizations experience.
0 — TensorFlow Fundamentals
Prologue to tensors (making tensors)
Getting data from tensors (tensor ascribes)
Controlling tensors (tensor activities)
Tensors and NumPy
Utilizing @tf.function (a method for accelerating your ordinary Python capabilities)
Utilizing GPUs with TensorFlow
1 — Neural Network Regression with TensorFlow
Construct TensorFlow successive models with numerous layers
Get ready information for use with a machine learning model
Get familiar with the various parts which make up a deep learning model (misfortune capability, engineering, streamlining capability)
Figure out how to analyze a regression issue (foreseeing a number) and construct a neural network for it
2 — Neural Network Classification with TensorFlow
Figure out how to analyze a classification issue (foreseeing whether something is one of several things)
Construct, accumulate and train machine learning classification models utilizing TensorFlow
Construct and train models for twofold and multi-class classification
Plot demonstrating execution measurements against one another
Match input (training information shape) and result shapes (expectation information target)
3 — Computer Vision and Convolutional Neural Networks with TensorFlow
Fabricate convolutional neural networks with Conv2D and pooling layers
Figure out how to analyze various types of computer vision issues
Figure out how to how to construct computer vision neural networks
Figure out how to utilize true images with your computer vision models
4 — Transfer Learning with TensorFlow Section 1: Feature Extraction
Figure out how to utilize pre-trained models to extricate features from your own information
Figure out how to involve TensorFlow Center for pre-trained models
Figure out how to utilize TensorBoard to think about the presentation of a few unique models
5 — Transfer Learning with TensorFlow Section 2: Fine-tuning
Figure out how to setup and run a few machine learning tests
Figure out how to utilize information expansion to expand the variety of your training information
Figure out how to fine-tune a pre-trained model to your own custom issue
Figure out how to utilize Callbacks to add usefulness to your model during training
6 — Transfer Learning with TensorFlow Section 3: Scaling Up (Food Vision mini)
Figure out how to increase a current model
Figure out how to how assess your machine learning models by tracking down the most off-base expectations
Beat the first Food101 paper utilizing just 10% of the information
7 — Milestone Project 1: Food Vision
Join all that you've learned in the past 6 journals to fabricate Food Vision: a computer vision model ready to characterize 101 various types of foods. Our model well and genuinely beats the first Food101 paper.
8 — NLP Fundamentals in TensorFlow
Figure out how to:
Preprocess natural language text to be utilized with a neural network
Make word embeddings (mathematical portrayals of text) with TensorFlow
Assemble neural networks equipped for twofold and multi-class classification utilizing:
RNNs (intermittent neural networks)
LSTMs (long momentary memory cells)
GRUs (gated repetitive units)
Figure out how to assess your NLP models
9 — Milestone Project 2: SkimLit
Repeat a the model which drives the PubMed 200k paper to characterize various successions in PubMed clinical modified works (which can assist specialists with perusing clinical edited compositions quicker)
10 — Time Series fundamentals in TensorFlow
Figure out how to analyze a time series issue (fabricating a model to make forecasts in light of information across time, for example foreseeing the stock cost of AAPL tomorrow)
Plan information for time series neural networks (features and names)
Understanding and utilizing different time series assessment techniques
MAE — mean outright blunder
Fabricate time series forecasting models with TensorFlow
RNNs (repetitive neural networks)
CNNs (convolutional neural networks)
11 — Milestone Project 3: (Shock)
Assuming you've perused this far, you are likely inspired by the course. This last project will be great.. we guarantee you, so see you inside the course ;)
TensorFlow is filling in fame and the sky is the limit from there and more employment opportunities are showing up for this particular information. Truly, TensorFlow is growing out of other well known ML apparatuses like PyTorch in work market. Google, Airbnb, Uber, DeepMind, Intel, IBM, Twitter, and numerous others are presently fueled by TensorFlow. There is an explanation these large tech organizations are utilizing this innovation and you will figure out about the power that TensorFlow gives developers.
We promise you this is the most exhaustive internet based seminar on passing the TensorFlow Developer Certificate to qualify you as a TensorFlow master. So why wait? Make yourself stand apart by turning into a Google Certified Developer and advance your profession.
See you inside the course!
Who this course is for:
Any individual who needs to breeze through the TensorFlow Developer test so they can join Google's Certificate Network and show their certificate and identifications on their resume, GitHub, and virtual entertainment stages including LinkedIn, making it simple to impart their degree of TensorFlow skill to the world
Understudies, developers, and information researchers who need to show viable machine learning abilities through the structure and training of models utilizing TensorFlow
Anybody hoping to extend their insight with regards to AI, Machine Learning and Deep Learning
Anybody hoping to dominate building ML models with the most recent form of TensorFlow
Organizer behind zerotomastery.io
Andrei is the teacher of the absolute most noteworthy appraised programming and specialized courses on the web. He is currently the organizer behind ZTM Foundation which is one of the quickest developing schooling stages on the planet. ZTM Foundation is known for having the absolute best educators and achievement rates for understudies. His alumni have continued on toward work for probably the greatest tech organizations all over the planet like Apple, Google, Tesla, Amazon, JP Morgan, IBM, UNIQLO and so on... He has been filling in as a senior programming developer in Silicon Valley and Toronto for a long time, and is currently taking all that he has learned, to show programming abilities and to assist you with finding the astounding profession potential open doors that being a developer permits throughout everyday life.
Having been a self trained developer, he comprehends that there is a staggering number of online courses, instructional exercises and books that are excessively verbose and deficient at showing legitimate abilities. The vast majority feel incapacitated and don't have the foggiest idea where to begin while learning a perplexing topic, or surprisingly more dreadful, a great many people don't have $20,000 to spend on a coding bootcamp. Programming abilities ought to be reasonable and open to all. Instruction material ought to show genuine abilities that are current and they shouldn't burn through an understudy's significant time. Having gained significant examples from working for Fortune 500 organizations, tech startups, to establishing his own business, he is currently devoting
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