TensorFlow for Deep Learning Bootcamp | Udemy
English | Size: 32.23 GB
Genre: eLearning[/center]
Learn TensorFlow by Google. Become an AI, Machine Learning, and Deep Learning expert!
What you'll learn
Build TensorFlow models using Computer Vision, Convolutional Neural Networks and Natural Language Processing
Complete access to ALL interactive notebooks and ALL course slides as downloadable guides
Increase your skills in Machine Learning, Artificial Intelligence, and Deep Learning
Understand how to integrate Machine Learning into tools and applications
Learn to build all types of Machine Learning Models using the latest TensorFlow 2
Build image recognition, text recognition algorithms with deep neural networks and convolutional neural networks
Using real world images to visualize the journey of an image through convolutions to understand how a computer "sees" information, plot loss and accuracy
Applying Deep Learning for Time Series Forecasting
Gain the skills you need to become a TensorFlow Developer
Be recognized as a top candidate for recruiters seeking TensorFlow developers
Just launched with all modern best practices for building neural networks with TensorFlow and becoming a TensorFlow & Deep Learning Expert!
Join a live online community of over 900,000+ students and a course taught by a TensorFlow expert. This course will take you from absolute beginner with TensorFlow, to creating state-of-the-art deep learning neural networks.
TensorFlow experts earn up to $204,000 USD a year, with the average salary hovering around $148,000 USD. By taking this course you will be joining the growing Machine Learning industry and becoming a top paid TensorFlow Developer!
Here is a full course breakdown of everything we will teach (yes, it's very comprehensive, but don't be intimidated, as we will teach you everything from scratch!):
The goal of this course is to teach you all the skills necessary for you to become a top 10% TensorFlow Developer.
This course will be very hands on and project based. You won't just be staring at us teach, but you will actually get to experiment, do exercises, and build machine learning models and projects to mimic real life scenarios. By the end of it all, you will develop skillsets needed to develop modern deep learning solutions that big tech companies encounter.
0 - TensorFlow Fundamentals
Introduction to tensors (creating tensors)
Getting information from tensors (tensor attributes)
Manipulating tensors (tensor operations)
Tensors and NumPy
Using @tf.function (a way to speed up your regular Python functions)
Using GPUs with TensorFlow
1 - Neural Network Regression with TensorFlow
Build TensorFlow sequential models with multiple layers
Prepare data for use with a machine learning model
Learn the different components which make up a deep learning model (loss function, architecture, optimization function)
Learn how to diagnose a regression problem (predicting a number) and build a neural network for it
2 - Neural Network Classification with TensorFlow
Learn how to diagnose a classification problem (predicting whether something is one thing or another)
Build, compile & train machine learning classification models using TensorFlow
Build and train models for binary and multi-class classification
Plot modelling performance metrics against each other
Match input (training data shape) and output shapes (prediction data target)
3 - Computer Vision and Convolutional Neural Networks with TensorFlow
Build convolutional neural networks with Conv2D and pooling layers
Learn how to diagnose different kinds of computer vision problems
Learn to how to build computer vision neural networks
Learn how to use real-world images with your computer vision models
4 - Transfer Learning with TensorFlow Part 1: Feature Extraction
Learn how to use pre-trained models to extract features from your own data
Learn how to use TensorFlow Hub for pre-trained models
Learn how to use TensorBoard to compare the performance of several different models
5 - Transfer Learning with TensorFlow Part 2: Fine-tuning
Learn how to setup and run several machine learning experiments
Learn how to use data augmentation to increase the diversity of your training data
Learn how to fine-tune a pre-trained model to your own custom problem
Learn how to use Callbacks to add functionality to your model during training
6 - Transfer Learning with TensorFlow Part 3: Scaling Up (Food Vision mini)
Learn how to scale up an existing model
Learn to how evaluate your machine learning models by finding the most wrong predictions
Beat the original Food101 paper using only 10% of the data
7 - Milestone Project 1: Food Vision
Combine everything you've learned in the previous 6 notebooks to build Food Vision: a computer vision model able to classify 101 different kinds of foods. Our model well and truly beats the original Food101 paper.
8 - NLP Fundamentals in TensorFlow
Learn to:
Preprocess natural language text to be used with a neural network
Create word embeddings (numerical representations of text) with TensorFlow
Build neural networks capable of binary and multi-class classification using:
RNNs (recurrent neural networks)
LSTMs (long short-term memory cells)
GRUs (gated recurrent units)
CNNs
Learn how to evaluate your NLP models
9 - Milestone Project 2: SkimLit
Replicate a the model which powers the PubMed 200k paper to classify different sequences in PubMed medical abstracts (which can help researchers read through medical abstracts faster)
10 - Time Series fundamentals in TensorFlow
Learn how to diagnose a time series problem (building a model to make predictions based on data across time, e.g. predicting the stock price of AAPL tomorrow)
Prepare data for time series neural networks (features and labels)
Understanding and using different time series evaluation methods
MAE - mean absolute error
Build time series forecasting models with TensorFlow
RNNs (recurrent neural networks)
CNNs (convolutional neural networks)
11 - Milestone Project 3: (Surprise)
If you've read this far, you are probably interested in the course. This last project will be good... we promise you, so see you inside the course 
TensorFlow is growing in popularity and more and more job openings are appearing for this specialized knowledge. As a matter of fact, TensorFlow is outgrowing other popular ML tools like PyTorch in job market. Google, Airbnb, Uber, DeepMind, Intel, IBM, Twitter, and many others are currently powered by TensorFlow. There is a reason these big tech companies are using this technology and you will find out all about the power that TensorFlow gives developers.
We guarantee you this is the most comprehensive online course on TensorFlow. So why wait? Make yourself stand out by becoming a TensorFlow Expert and advance your career.
See you inside the course!
Who this course is for:
Anyone who wants to become a top 10% TensorFlow Developer and be at the forefront of Artificial Intelligence, Machine Learning, and Deep Learning
Students, developers, and data scientists who want to demonstrate practical machine learning skills through the building and training of models using TensorFlow
Anyone looking to expand their knowledge when it comes to AI, Machine Learning and Deep Learning
Anyone looking to master building ML models with the latest version of TensorFlow
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