Resource of free step by step video how to guides to get you started with machine learning.
Thursday, June 16, 2022
Python TensorFlow for Machine Learning – Neural Network Text Classification Tutorial
This course will give you an introduction to machine learning concepts and neural network implementation using Python and TensorFlow. Kylie Ying explains basic concepts, such as classification, regression, training/validation/test datasets, loss functions, neural networks, and model training. She then demonstrates how to implement a feedforward neural network to predict whether someone has diabetes, as well as two different neural net architectures to classify wine reviews. ✏️ Course created by Kylie Ying. 🎥 YouTube: https://youtube.com/ycubed 🐦 Twitter: https://twitter.com/kylieyying 📷 Instagram: https://instagram.com/kylieyying/ This course was made possible by a grant from Google's TensorFlow team. ⭐️ Resources ⭐️ 💻 Datasets: https://drive.google.com/drive/folders/1YnxDqNIqM2Xr1Dlgv5pYsE6dYJ9MGxcM?usp=sharing 💻 Feedforward NN colab notebook: https://colab.research.google.com/drive/1UxmeNX_MaIO0ni26cg9H6mtJcRFafWiR?usp=sharing 💻 Wine review colab notebook: https://colab.research.google.com/drive/1yO7EgCYSN3KW8hzDTz809nzNmacjBBXX?usp=sharing ⭐️ Course Contents ⭐️ ⌨️ (0:00:00) Introduction ⌨️ (0:00:34) Colab intro (importing wine dataset) ⌨️ (0:07:48) What is machine learning? ⌨️ (0:14:00) Features (inputs) ⌨️ (0:20:22) Outputs (predictions) ⌨️ (0:25:05) Anatomy of a dataset ⌨️ (0:30:22) Assessing performance ⌨️ (0:35:01) Neural nets ⌨️ (0:48:50) Tensorflow ⌨️ (0:50:45) Colab (feedforward network using diabetes dataset) ⌨️ (1:21:15) Recurrent neural networks ⌨️ (1:26:20) Colab (text classification networks using wine dataset) -- 🎉 Thanks to our Champion and Sponsor supporters: 👾 Raymond Odero 👾 Agustín Kussrow 👾 aldo ferretti 👾 Otis Morgan 👾 DeezMaster -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news And subscribe for new videos on technology every day: https://youtube.com/subscription_center?add_user=freecodecamp
Subscribe to:
Post Comments (Atom)
-
JavaやC++で作成された具体的なルールに従って動く従来のプログラムと違い、機械学習はデータからルール自体を推測するシステムです。機械学習は具体的にどのようなコードで構成されているでしょうか? 機械学習ゼロからヒーローへの第一部ではそのような疑問に応えるため、ガイドのチャー...
-
Using GPUs in TensorFlow, TensorBoard in notebooks, finding new datasets, & more! (#AskTensorFlow) [Collection] In a special live ep...
-
#minecraft #neuralnetwork #backpropagation I built an analog neural network in vanilla Minecraft without any mods or command blocks. The n...
-
Using More Data - Deep Learning with Neural Networks and TensorFlow part 8 [Collection] Welcome to part eight of the Deep Learning with ...
-
Linear Algebra Tutorial on the Determinant of a Matrix 🤖Welcome to our Linear Algebra for AI tutorial! This tutorial is designed for both...
-
STUMPY is a robust and scalable Python library for computing a matrix profile, which can create valuable insights about our time series. STU...
-
❤️ Check out Fully Connected by Weights & Biases: https://wandb.me/papers 📝 The paper "Alias-Free GAN" is available here: h...
-
Why are humans so good at video games? Maybe it's because a lot of games are designed with humans in mind. What happens if we change t...
-
Visual scenes are often comprised of sets of independent objects. Yet, current vision models make no assumptions about the nature of the p...
-
#ai #attention #transformer #deeplearning Transformers are famous for two things: Their superior performance and their insane requirements...
No comments:
Post a Comment