50 Concepts, Algorithms in Machine Learning You Should Know. Introduction to 50 Must know Topics of Machine Learning, Data science. Understand machine Learning Syllabus. Introduction to must know concepts in Machine Learning which will help you to prepare for interview. Learn how to Learn Machine Learning. You will get an idea of complete syllabus in Machine Learning. Improve or refresh knowledge in Machine Learning50 Concepts, Algorithms in Machine Learning You Should Know
This course is designed to give you introduction to syllabus of machine learning. If you want to get started with machine learning then this course will help you. It helps you to get ready for an interview with 50 concepts covering varied range of topics. The course is intended not only for candidates with a full understanding of Machine Learning but also for recalling knowledge in data science.
What you'll learn
This Edureka video on 'Python For Data Science - How to use Data Science with Python - Data Science using Python ' will help you understand how we can use python for data science along with various use cases. What is Data Science? Why Python? Python Libraries For Data Science. Roadmap To Data Science With Python. Data Science Jobs and Salary Trends
This Edureka video on 'Python For Data Science - How to use Data Science with Python - Data Science using Python
' will help you understand how we can use python for data science along with various use cases. Following are the topics discussed this Python Data Science Tutorial:
Complete hands-on Machine Learning tutorial with Data Science, Tensorflow, Artificial Intelligence, and Neural Networks. Introducing Tensorflow, Using Tensorflow, Introducing Keras, Using Keras, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Learning Deep Learning, Machine Learning with Neural Networks, Deep Learning Tutorial with PythonMachine Learning, Data Science and Deep Learning with Python
Explore the full course on Udemy (special discount included in the link): http://learnstartup.net/p/BkS5nEmZg
In less than 3 hours, you can understand the theory behind modern artificial intelligence, and apply it with several hands-on examples. This is machine learning on steroids! Find out why everyone’s so excited about it and how it really works – and what modern AI can and cannot really do.
In this course, we will cover:
• Deep Learning Pre-requistes (gradient descent, autodiff, softmax)
• The History of Artificial Neural Networks
• Deep Learning in the Tensorflow Playground
• Deep Learning Details
• Introducing Tensorflow
• Using Tensorflow
• Introducing Keras
• Using Keras to Predict Political Parties
• Convolutional Neural Networks (CNNs)
• Using CNNs for Handwriting Recognition
• Recurrent Neural Networks (RNNs)
• Using a RNN for Sentiment Analysis
• The Ethics of Deep Learning
• Learning More about Deep Learning
At the end, you will have a final challenge to create your own deep learning / machine learning system to predict whether real mammogram results are benign or malignant, using your own artificial neural network you have learned to code from scratch with Python.
Separate the reality of modern AI from the hype – by learning about deep learning, well, deeply. You will need some familiarity with Python and linear algebra to follow along, but if you have that experience, you will find that neural networks are not as complicated as they sound. And how they actually work is quite elegant!
This is hands-on tutorial with real code you can download, study, and run yourself.
This video will focus on the top Python libraries that you should know to master Data Science and Machine Learning. Here’s a list of topics that are covered in this session:
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