Top Videos And Tutorials To Get Started With Machine Learning And Artificial Intelligence at Beginner Level, Part-1

By Jyoti Nigania |Email | Oct 6, 2018 | 15111 Views

In Part-1 we are covering how to learn Machine Learning at Beginners level. Machine Learning and Artificial Intelligence are the two most trending technology everyone want to get learn and get started their career in these field. This field is not only in demand but also the highest paid profile. Here if you are at beginner level to learn machine learning and artificial intelligence follow these videos as you can gain more insights to start your career.
In this article, I have compiled popular and most viewed machine learning videos, tutorials and courses of Machine Learning and Artificial Intelligence. It helps you to get started with machine learning and gain expertise building predictive models using machine learning.
To get start your career in Machine Learning And Artificial Intelligence it is divided into 3 levels:
  • Machine Learning for Beginners
  • Machine Learning: Advanced
  • Application of Machine Learning
Machine Learning For Beginners
1.How to become a Data Scientist in 6 months:
In this video, Tetiana Ivanova shares her journey of becoming a data scientist in just 6 months. Participating in hackathons got her started with machine learning. If you have been wondering whether to go for analytics post-graduate program or become self-taught data science professional, you must watch this video. Tetiana shares her real life experience of making the career move, the hardships and truth behind the facade of a higher education. Either you are a beginner or someone transitioning his / her career to data science then I would recommend that you must watch this video. This video will leave you inspired.
2. Statistical Machine Learning Course:
In this course from Carnegie Mellon University, it will take you through basics of machine learning and statistical modeling. You will learn about parametric &  non-parametric regression, clustering, boosting, graphical methods, minimax theory, dimensionality reduction, etc. This course is best suited for students with a sound background in statistics & mathematics. Alongside, there are assignments & solution which would further improve your concepts. Feel free to skip the initial few minutes of the first video.
3. Machine Learning Course:
This course on machine learning from the University of Waterloo will take you through machine learning basics and advanced concepts. It's a conceptual course which will educate you on mathematical relations in ML algorithms. It has been taught by multiple professors including Shai Ben David, author of book Understanding machine learning. It covers topics such as linear regression, bayesian, trees, clustering, neural networks, ensemble, hidden markov model and much more. Check out the other course material here. Feel free to skip the first 8 mins of the video.
4. Practical Machine Learning Tutorial with Python:
This course is designed for all the Python practitioners looking for a comprehensive introduction to machine learning. It covers theoretical & practical concepts on supervised, unsupervised and deep learning algorithms. In this series of videos, you will learn about linear regression, K-Nearest Neighbors, Support Vector Machines (SVM), flat clustering, hierarchical clustering, and neural networks. For each algorithm, the speaker discusses the real-life applications with the help of actual data sets. Then you will learn about the workings of each of the algorithms by recreating them in code. This will provide you a complete understanding of exactly how the algorithms work, how they can be tweaked to our advantage.
5. Introduction-Learn Python for Data Science:
Here's yet another tutorial to learn Python for data science. If your hectic work schedule has been making it difficult for you to start with learning data science then these videos are at your rescue. In these 7 min videos, you will learn how to get started with data science. It will introduce you to sentimental analysis, recommendation system, predicting stock prices, create neural network using python & tensor flow and introduction to genetic algorithms. The speaker is clear in his approach and will let you learn data science in your tea breaks. This tutorial requires basic understanding of Python.
6. Machine Learning Tutorial:
This is an exclusive tutorial by Sebastian Raschka and Andreas Muller from the SciPy Conference held in July 2016. In this tutorial, Sebastian introduces machine learning & Scikit Learn with sample applications. Then he will go on to explain the different computational tools for Python: NumPy, SciPy and matplotlib. Sebastian explains data representation using Iris data-set for machine learning. Andreas introduces you to classification and regression techniques in supervised learning. Sebastian then explains clustering technique for unsupervised learning and will make you familiar with the interface of scikit-learn, one of the widely used python libraries. It will also provide you hands-on experience in building a predictive model using Titanic data-set.
7. Data Analysis in Python with Pandas:
Pandas is full-featured Python library for data analysis, manipulation and visualization. With high its readability and general purpose use, Python is often a popular choice for beginners to start with data science. This tutorial is for Python users who want to understand the vast data and get started with data science. The series will introduce you to Pandas and what all you can do using Pandas library. In this 31 video series, the speaker will take you through each step of Pandas involved in data analysis.
8. Machine Learning-CS-50 2016:
This is a video from CS-50 course taught at Harvard and Yale University. In this video, the speaker introduces you to machine learning and its applications. For all coders out there this is one of the best tutorials for you to get started with machine learning using Python. It is a simple introduction to machine learning and it is affecting our lives today. Learn how machine learning is being applied for building search engines, image recognition, voice recognition, and natural language processing. This tutorial will teach you image classification with Python and text clustering. Skip the first 9:05 mins of the video.
9. Analyzing and Manipulating Data with Pandas Beginner:
As I described above, Pandas is one of the popular libraries in Python. This tutorial will take you through analyzing and manipulating data in Python using Pandas. Pandas ecosystem is growing more & more and it user friendliness makes data analysis simpler. This tutorial is aimed at any beginner who wants to get started with data analysis in Python. It uses climate data-sets to learn about Pandas.
10.What is Artificial Intelligence:
Artificial Intelligence is a means to make machines smart enough to take actions on their own. There is a lot of buzz around AI but people often ask the question what is AI exactly? Here is a brief video which takes you to the origin of AI. Learn how AI has evolved into a mainstream topic and how its various applications are changing the world. AI has created a possibility for machines to differentiate between a dog and a human. Learn what are expert systems and how image recognition, robotics, deep learning are all inter-connected with AI.
Learn how AI has evolved into a mainstream topic and how its various applications are changing the world. AI has created a possibility for machines to differentiate between a dog and a human. Learn what are expert systems and how image recognition, robotics, deep learning are all inter-connected with AI.

For more insights stay tuned with us, In Part-2 will discuss Machine Learning at an advanced level.

Source: HOB