Varied approaches to Machine Learning: Supervised & Unsupervised, Regression & Classifications, more.
Learn various advanced machine learning algorithms like KNN, Decision Trees, SVM, Clustering in detail.
Learn deep learning techniques, data visualization and how to build and deploy deep learning models.
Immersive applied learning to transform your theoretical knowledge into practical skill.Download Syllabus
Machine learning came into its own in the late 1990s, when data scientists hit upon the concept of training computers to think. Machine learning gives computers the capability to automatically learn from data without being explicitly programmed, and the capability of completing tasks on their own. This means in other words that these programs change their behaviour by learning from data. Machine learning enthusiasts are today among the most sought after professionals. Learn to build incredibly smart solutions that positively impact people’s lives, and make businesses more efficient! With Payscale putting average salaries of Machine Learning engineers at $115,034, this is definitely the space you want to be in!
Data is transforming everything we do. All organizations, from startups to tech giants to Fortune 500 corporations, are racing to harness the immense amounts of data generated unknowingly every day and put it to use for key decisions. Big and small data is reshaping technology and business as we know it and will continue to do so (in the near future at least).
The state of Machine Learning in companies and in your daily life machine Learning is no more just a mere niche of the tech world but is a new field of work and research altogether. Tech experts have been increasingly making use of Machine Learning over the years. Surge pricing at Uber, Walmart product recommendations, Social media feeds displayed by both Facebook and Instagram, Google Maps, detecting financial fraud at financial institutions etc - all these and many more functionalities are now being performed with the help of powerful Machine Learning algorithms, increasingly without human interference.Every individual is making use of one or the other product of Machine Learning, whether he knows it or not. In such a scenario, learning about Machine Learning is an inevitable step that any professional, especially someone involved in the field of Information Technology and Data Science, must take in order to not become irrelevant.
Some of the benefits of learning Machine Learning include the following:
|Statistical analysis concepts||14:02||Play|
|Introduction to probability and Bayes theorem||14:02||Play|
|Hypothesis testing & scores||14:02||Play|
|Pandas for pre-Processing and Exploratory Data Analysis||14:03||Play|
|Numpy for Statistical Analysis||14:03||Play|
|Matplotlib & Seaborn for Data Visualization||14:03||Play|
|Machine Learning Modelling Flow||14:06||Play|
|How to treat Data in ML||14:06||Play|
|Types of Machine Learning||14:06||Play|
|Overfitting & Underfitting||14:07||Play|
|Maxima and Minima||14:08||Play|
|Naive Bayesian classifiers||14:11||Play|
|SVM - Support Vector Machines||14:11||Play|
|K Means clustering||14:12||Play|
|Introduction to Ensemble Learning||14:15||Play|
|Different Ensemble Learning Techniques||14:15||Play|
|PCA (Principal Component Analysis) and Its Applications||14:15||Play|
|Introduction to Recommendation Systems||14:17||Play|
|Types of Recommendation Techniques||14:17||Play|
|Content based Filtering||14:18||Play|
Wissenhive's Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. Machine Learning training will provide a deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in the python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real-life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in the python programming language to enhance your learning experience.
Wissenhive's Python Machine Learning Certification Course is a good fit for the below professionals:
No exam required.
The candidate will complete a project at the end of the training. On successful completion of the project the candidate will receive a certificate of training.
Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.
The concept of Machine Learning deals with computers and systems taking in a huge amount of data, analyzing it and solving problems through training on that data in order to obtain the best possible outcome for a task or problem. It is a way for humans to be able to solve problems, without having to actually know and understand what the problem really is, as well as why a particular approach to a problem actually works.