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
Labels:
AI how to,
Learn machine learning,
machine learning Tutorial,
supervised learning tutorial,
Tutorial
Published by Free artificial intelligence and machine learning video tutorial resource
Related video tutorials
Subscribe to:
Post Comments (Atom)
Most watched
-
Quick answer: Qwen 3 32B needs about 22.7 GB of VRAM at Q4_K_M with a 4k-token context — a used 24 GB card like the RTX 3090 is the minimu...
-
Using GPUs in TensorFlow, TensorBoard in notebooks, finding new datasets, & more! (#AskTensorFlow) [Collection] In a special live ep...
-
Inside TensorFlow: Summaries and TensorBoard [Collection] Take an inside look into the TensorFlow team’s own internal training sessions-...
-
Quick answer: DeepSeek V4 Flash is a Mixture-of-Experts model: all 284 billion parameters must be stored, so combined RAM plus VRAM — not ...
-
Quick answer: For an 8B model at Q4, local electricity costs roughly $0.05 per million output tokens — against about $0.53 per million ble...
-
Hey everyone This is Ujjwal kapil B.tech 2nd year Ai and Ml In this video we covered one of the most important question "COLLEGE KAB O...
-
Quick answer: For machine-learning work, buy an external SSD over a spinning hard drive, pick USB 3.2 Gen 2 (10 Gbps) or faster, and size f...
-
Quick answer: Yes, for most budget builders: a used RTX 3090 is still the cheapest route to 24 GB of VRAM with full CUDA support. Capacity...
-
This video is a crash course on understanding how finetuning on LLM models can be performed uing QLORA,LORA, Quantization using LLama2, Grad...
-
In this video, you'll learn how to use machine learning, computer vision and deep learning to create a football analysis system. This pr...
No comments:
Post a Comment