Quick to Production with Minimal MLOps with the Best of Spark and TensorFlow
In this session, learn how we can get deep learning and ml models with TensorFlow into production quickly right after prototyping. Using TensorFlow with big datasets in a distributed setting has been an issue for small teams like ours due to complicated MLOps code, but with what we cover in the talk, we could now […]
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Deep Learning with TensorFlow – Course Reflection
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Frank
- May 9, 2022
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- Clustering
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- Sequential model
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- TFJS
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
Here’s the final video on DeepLizard’s Deep Learning with TensorFlow course.
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Tensorflow Object Detection in 5 Hours with Python
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Frank
- January 26, 2022
- Object Detection
- object detection python
- object detection raspberry pi
- object detection tensorflow
- object detection tensorflow 2.0
- object detection tutorial
- object detection using tensorflow
- tensorflow object detection
- tensorflow object detection api
- tensorflow object detection api google colab
- tensorflow object detection raspberry pi
- tensorflow object detection tutorial
- tensorflow object detection tutorial for beginners
- tensorflow object detection with python
Want to get up to speed on AI powered Object Detection but not sure where to start? Want to start building your own deep learning Object Detection models? This is the course you need! In this course, you’ll learn everything you need to know to go from beginner to practitioner when it comes to deep […]
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Introduction to object detection on Raspberry Pi
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Frank
- December 13, 2021
- AI
- edge AI
- GDS: Yes
- Google Developers
- Machine Learning for Raspberry Pi
- ML for Raspberry Pi
- Object Detection
- object detection model
- pr_pr: TensorFlow
- pre-trained ML model
- pre-trained object detection
- purpose: Educate
- Raspberry Pi
- series: Coding TensorFlow
- TensorFlow
- tensorflow developer
- tensorflow developers
- Tensorflow light
- TensorFlow Lite
- TF Lite
- TFX
- type: DevByte (deck cleanup 0-10min)
In the first episode of Machine Learning for Raspberry Pi, learn how to download a pre-trained TensorFlow Lite object detection model and deploy it to your Raspberry Pi. This model can be used to recognize general objects such as an apple, a television, or a car.
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Finishing the Tensorflow.js Autoencoder project
The Coding Train wraps up his series on the TensorFlow.js autoencoder.
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Keras Full Course for Beginners
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Frank
- September 1, 2021
- deep learning and neural networks
- deep learning with keras
- deep learning with keras and tensorflow
- Keras
- keras example
- keras example python
- keras explained
- keras explanation
- keras full course
- keras full tutorial
- keras tutorial
- keras tutorial for beginners
- learn keras
- learn keras for deep neural networks
- learn keras from scratch
- learn keras python
- simplilearn
- simplilearn keras
- what are neural networks
- what is keras
- what is keras and tensorflow
Keras is a high-level, deep learning API developed by Google for implementing neural networks. Written in Python, it is used to make the implementation of neural networks easy. Keras is relatively easy to learn and work with because it provides a python frontend with a high level of abstraction while having the option of multiple […]
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Text Classification Using BERT & Tensorflow
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Frank
- August 29, 2021
- bert model
- bert model nlp python
- BERT text classification
- BERT tutorial
- deep learning tutorial
- deep learning tutorial for beginners
- kera tutorial
- neural network python tutorial
- python deep learning example
- python deep learning tensorflow
- python deep learning tutorial
- tensorflow 2.0 tutorial python
- tensorflow bert
- tensorflow bert tutorial
- tensorflow tutorial
- tensorflow tutorial for beginners
Using BERT and Tensorflow 2.0, we will write simple code to classify emails as spam or not spam. BERT will be used to generate sentence encoding for all emails and after that we will use a simple neural network with one drop out layer and one output layer.
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‘CARLA’ Python Library for Benchmarking Counterfactual Explanation Methods Across Data Sets and Machine Learning Models
Researchers at the University of Tübingen are unveiling a new python library CARLA (Counterfactual And Recourse LibrAry) which will allow for benchmarking counterfactual explanation methods across different data sets and machines. CARLA is an innovative open-source library that allows researchers to benchmark predictive counterfactual explanation and recourse CE methods for managing uncertainty in their analyses. […]
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How to make TensorFlow models run faster on GPUs
XLA compilation on GPU can greatly boost the performance of your models, Learn how to use @tf.function(jit_compile=True) in TensorFlow to control what exact scopes are being compiled, and how to debug the performance of the resulting program. We’ll cover writing compiled models, debugging them, and exploring the performance characteristics and optimizations the XLA compiler performs, […]
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7 Machine Learning Libraries for Aspiring Experts
Machine learning has become the center of discussion in artificial intelligence today. It touches all fields, including engineering, medicine, business, social science, and just about everything else. Here’s a list of the most important libraries as compiled by www.makeuseof.com
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