What Will You Learn?
In the Machine Learning with Python Course, you'll use the TensorFlow framework to build several neural networks and explore more advanced techniques like natural language processing and reinforcement learning.
You'll also dive into neural networks, and learn the principles behind how deep, recurrent, and convolutional neural networks work.
About This Course
Provider: Freecodecamp
Format: Online
Duration: 300 hours to complete [Approx]
Target Audience: Beginners
Learning Objectives: After completing this free course, you'll master TensorFlow for building neural networks, delve into advanced techniques like natural language processing and reinforcement learning.
Course Prerequisites: NA
Assessment and Certification: Earn a Certificate upon completion from the relevant Provider
Instructor: Freecodecamp
Key Topics: Python Programming Language, Tensorflow, Neural Networks, Machine Learning, Deep Learning, Natural Language Processing
Topic Covered:
- - Introduction: Machine Learning Fundamentals
- - Introduction to TensorFlow
- - Core Learning Algorithms
- - Core Learning Algorithms: Working with Data
- - Core Learning Algorithms: Training and Testing Data
- - Core Learning Algorithms: The Training Process
- - Core Learning Algorithms: Classification
- - Core Learning Algorithms: Building the Model
- - Core Learning Algorithms: Clustering
- - Core Learning Algorithms: Hidden Markov Models
- - Core Learning Algorithms: Using Probabilities to make Predictions
- - Neural Networks with TensorFlow
- - Neural Networks: Activation Functions
- - Neural Networks: Optimizers
- - Neural Networks: Creating a Model
- - Convolutional Neural Networks
- - Convolutional Neural Networks: The Convolutional Layer
- - Creating a Convolutional Neural Network
- - Convolutional Neural Networks: Evaluating the Model
- - Convolutional Neural Networks: Picking a Pretrained Model
- - Natural Language Processing With RNNs
- - Natural Language Processing With RNNs: Recurring Neural Networks
- - Natural Language Processing With RNNs: Sentiment Analysis
- - Natural Language Processing With RNNs: Making Predictions
- - Natural Language Processing With RNNs: Create a Play Generator
- - Natural Language Processing With RNNs: Building the Model
- - Natural Language Processing With RNNs: Training the Model
- - Reinforcement Learning With Q-Learning
- - Reinforcement Learning With Q-Learning: Example
- - How Neural Networks Work
- - How Deep Neural Networks Work
- - Recurrent Neural Networks RNN and Long Short Term Memory LSTM
- - Deep Learning Demystified
- - How Convolutional Neural Networks work
- - Project 1: Rock Paper Scissors
- - Project 2: Cat and Dog Image Classifier
- - Project 3: Book Recommendation Engine using KNN
- - Project 4: Linear Regression Health Costs Calculator
- - Project 5: Neural Network SMS Text Classifier
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