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 Python

Machine Learning, Data Science and Deep Learning with PythonExplore 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.

What is Artificial Intelligence (AI)? AI is the ability of a machine to think like human, learn and perform tasks like a human. Know the future of AI, Examples of AI and who provides the course of Artificial Intelligence?

US and China are massively investing in Artificial Intelligence which create a promising career in the field. One of the first steps to a successful artificial Intelligence career is to learn the basics around the domain. Articles and Guides are your opening friends towards a successful AI Career. Read on to know more.

This video on Data Science is a full course compilation that will help you gain all the concepts, techniques, and algorithms involved in data science. Python and R are the primary programming languages used for data science.

**Data Science Full Course | Data Science For Beginners | Learn Data Science In 10 Hours**

Here, you will *understand *the *basics *of **data science**, such as ** data munging, data mining,** and

You will get an idea about the salary, skills, jobs, and resume of a data scientist (9:00:04).

Finally, you will *learn *about the important ** data science interview questions** (9:04:42) that would help you crack any

**Below topics are explained in this Data Science tutorial:**

1. Data Science basics (01:28)

2. What is Data Science (05:51)

3. Need for Data Science (06:38)

4. Business intelligence vs Data Science (17:30)

5. Prerequisites for Data Science (22:31)

6. What does a Data Scientist do? (30:23)

7. Demand for Data Scientist (53:03)

8. Linear regression (2:30:10)

9. Decision trees (2:53:39)

10. Logistic regression in R (3:09:12)

11. What is a decision tree? (3:27:04)

12. What is clustering? (4:35:40)

13. Divisive clustering (4:51:14)

14. Support vector machine (5:17:21)

15. K-means clustering 96:44:13)

16. Time series analysis (7:33:05)

17. How to become a Data Scientist (8:26:54)

18. Job roles in Data Science (8:30:59)

19. Simplilearn certifications in Data Science (8:33:50)

20. Who is a Data Science engineer? (8:34:34)

21. Data Science engineer resume (9:00:04)

22. Data Science interview questions and answers (9:04:42)