Machine Learning from A to Z with examples (Pre-Launched)

Description

Machine learning is the study of computer algorithms that improve automatically through experience, it's one of the most well-liked and top paying skills. Machine learning is also one of the most interesting fields to work on. They are typically used to solve various types of life problems. In the older days, Machine Learning tasks were time-consuming, tedious, and inefficient. In the modern days, it’s become considerably easy and efficient compared to the olden days by various Python libraries, frameworks, and modules.

What makes ML so popular to learn?

In this technology-reliant world, we are gradually traversing towards new and better processing techniques. As a result, to sustain the hunger for technology machine learning is considered as its answer. ML is one of the technologies which is expected to revolutionize the future. From trivial jobs to sophisticated services, everything is using ML today. Machine learning is not just learning but it’s also about understanding and reasoning. It is one of the widely used techniques to apply complex algorithms on a particular dataset to create a model for a data science project.

If you're curious about the sector of Machine Learning? Then this course is for you!

In this course, we'll cover all concepts, functions, and required topics which will assist you with learning complex algorithms, calculations, and coding libraries in a basic and straightforward manner and prepare you for an entry into this hot career path. Here you'll learn step by step, and in each tutorial, you'll build up new skills and may improve your understanding of machine learning. If you've got some programming or scripting experience, this course clarifies things in a practical and simple to follow strategy that will allow you to understand what you are doing in no time.

Deep Learning

Deep Learning is one of the main aspects to be learned in the field of Data Science. Deep learning is considered as a subset of Machine Learning (ML) which by the way is also a subset of Artificial Intelligence (AI). All these three concepts are co-related to each other, but they are not the same. To be precise with definitions an Artificial Intelligence is a technique that enables a machine to mimic human behaviour. On the other hand, Machine Learning is defined as a technique to achieve AI through algorithms trained with data and finally, Deep Learning is a type of machine learning inspired by the structure of the human brain. In terms of Deep Learning this structure is called an Artificial Neural Network (ANN).

Learn a powerful skill at your home

This is the best course for Machine learning. Theoretical knowledge is not sufficient for machine learning. This course will allow you to practice machine learning concepts every day at home.

Practice makes man perfect and it all depends on your efforts and diligence.

Why Learn From Me

Machine learning course can be challenging and complex. To navigate this tangle, you need a simple and direct approach to the purpose. This course gives you my teaching experience and my knowledge of the industry. I have taught IT for more than seven years to more than 1, 40,000 students, all are happy.

I am also an application developer. Helping you master these issues is my highest priority. My teaching style is different from others and easy to understand because I usually take simple and straightforward examples and follow a step-by-step approach. If you find any difficulty in any video which I even have covered during this course please feel free to ask your doubt. I am always happy to help you.

No question asked - Money Back Guarantee!

There is no risk, this course comes with a 30-day money-back guarantee. Once you purchase the course, if for any reason you are not satisfied with the course, please let me know, I will refund 100%, no questions asked. So you've got nothing to lose, check-in for this course, and learn “Machine Learning from A to Z with examples!

At the end of the course, you’ll have great confidence. What are you waiting for?

Join me on this adventure today! See you on the course.

What you’ll learn

• The most effective method to dodge issues with Machine Learning, to effectively execute it without losing your brain!
• To realise what issues machine learning can illuminate, and how the Machine Learning process functions
• Use Python for Machine Learning
• Percentiles, moment and quantiles
• Learn to utilise Matplotlib for Python plotting
• Learn to utilise Seaborn for measurable plots
• Learn Advance mathematics for Machine Learning
• Understand matrix multiplication, Matrix operations, and scalar operations
• Use Pair plot and limitations
• Implement Identity matrix, matrix inverse properties, transpose of matrix, Vector multiplication
• Implement Linear Regression, Multiple Linear Regression, Polynomial Regression, Decision Tree Regression, Random Forest Regression
• AdaBoost and XGBoost regressor, SVM (regression) Background, SVR under Python
• ML Concept-k-Fold validation, GridSearch
• Classification-k-nearest neighbours’ algorithm (KNN)
• Gaussian Naive Bayes under python & visualization of models
• Learn evaluation techniques using curves (ROC, AUC, PR, CAP)
• Implement machine learning algorithms
• More topics coming soon

Who this course is for:

• Anyone curious about Machine Learning or AI
• Students who have a minimum of high school knowledge in math and who need to begin learning Machine Learning
• Anyone who isn't much comfortable with coding but who have an interest in Machine Learning and need to use it easily on datasets
• Anyone in college who want to start a career in Data Science
• Any data analysts who want to level up in Machine Learning
• Software developers or programmers who want to transition into the Machine Learning career path will learn tons from this course