01. What Is TensorFlow? | Practical ML with TensorFlow
Practical ML with TensorFlow
Learn practical machine learning and deep learning with TensorFlow and Keras by building real-world AI models from scratch. This series covers the complete machine learning workflow: Collect → Preprocess → Build → Train → Evaluate → Save → Deploy → Predict.
You'll learn the core concepts behind neural networks, computer vision, natural language processing (NLP), transformers, reinforcement learning, generative AI, and production deployment. Every episode explains the underlying ideas with clear animations, intuitive visuals, practical code examples, and real-world outputs.
▶ FULL COURSE CODE (Google Colab — runs in your browser, no setup):
https://github.com/kader-xai/ml-cours...
Open the TensorFlow notebook:
https://colab.research.google.com/git...
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COURSE OUTLINE
01 · What Is TensorFlow?
02 · Your First TensorFlow Model
03 · TensorFlow Data Pipelines
04 · Neural Networks with TensorFlow
05 · Loss Functions & Backpropagation
06 · Overfitting & Regularization
07 · Convolutional Neural Networks (CNNs)
08 · Transfer Learning
09 · Object Detection
10 · Optical Character Recognition (OCR)
11 · Text Embeddings
12 · Sentiment Analysis
13 · Recurrent Neural Networks (RNNs)
14 · Attention Mechanism
15 · Transformer Block
16 · Text Classification with Transformers
17 · Text Generation
18 · Machine Translation
19 · Fine-Tuning BERT
20 · Named Entity Recognition (NER)
21 · Time Series Forecasting
22 · Recommendation Systems
23 · Reinforcement Learning
24 · Generative AI (GANs, VAEs & Diffusion Models)
25 · Custom Training Loops
26 · Model Deployment
27 · TensorFlow Lite
28 · End-to-End AI Project
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MUSIC
"Reflections" by Vincent Rubinetti
from The Music of 3Blue1Brown (2018)
https://vincerubinetti.bandcamp.com
#TensorFlow #Keras #MachineLearning #DeepLearning #AI #Python #NLP #Transformers #ComputerVision