Key Highlights
contact us
+1 930 200 4823
( Toll Free )
25 Hrs Instructor Led Training
Self-paced Videos
20 Hrs Project & Exercises
Certification
Job Assistance
Flexible Schedule
Lifetime Free Upgrade
Mentor Support
Online | Self-Paced | Corporate
Machine Learning Training
By taking Machine learning (ML) training from Tekslate, you’ll become an expert in working with Artificial neural networks. This course enables you to gain in-depth knowledge of ML concepts and techniques. It will help you to develop skills on supervised and unsupervised learning and provides hands-on experience in modeling to develop algorithms and mathematical and heuristic aspects. Our curriculum is designed by industry experts based on real-time scenarios. You will get hands-on experience in ML by working on various real-time applications.
(4.8)
261 Learners
Curriculum
A complete index of
job-ready skills curated
to meet the industrial need.
Explore.
Introduction to Python
- Installation of Python framework and packages: Anaconda & pip
- Writing/Running python programs using Spyder Command Prompt
- Working with Jupyter notebooks
- Creating Python variables
- Numeric, string and logical operations
Iterative Operations & Functions in Python
- Writing for loops in Python
- While loops and conditional blocks
- List/Dictionary comprehensions with loops
- Writing your own functions in Python
- Writing your own classes and functions
Data summary & visualization in Python
- Need for data summary & visualization
- Summarising numeric data in pandas
- Summarising categorical data
- Group-wise summary of mixed data
- Basics of visualization with ggplot & Seaborn
- Inferential visualization with Seaborn
- Visual summary of different data combinations
Data Handling in Python using NumPy & Pandas
- Introduction to NumPy arrays, functions & properties
- Introduction to Pandas & data frames
- Importing and exporting external data in Python
- Feature engineering using Python
Generalized Linear Models in Python
- Linear Regression
- Regularisation of Generalised Linear Models
- Ridge and Lasso Regression
- Logistic Regression
- Methods of threshold determination and performance measures for classification score models
Tree Models using Python
- Introduction to decision trees
- Tuning tree size with cross-validation
- Introduction to bagging algorithm
- Random Forests
- Grid search and randomized grid search
- ExtraTrees (Extremely Randomised Trees)
- Partial dependence plots
Boosting Algorithms using Python
- The concept of weak learners
- Introduction to boosting algorithms
- Adaptive Boosting
- Extreme Gradient Boosting (XGBoost)
Machine Learning Basics
- Converting business problems to data problems
- Understanding supervised and unsupervised learning with examples
- Understanding biases associated with any machine learning algorithm
- Ways of reducing bias and increasing generalization capabilities
- Drivers of machine learning algorithms
- Cost functions
- Brief introduction to gradient descent
- Importance of model validation
- Methods of model validation
- Cross-validation & average error
Support Vector Machines (SVM) & kNN in Python
- Introduction to idea of observation-based learning
- Distances and similarities
- k Nearest Neighbours (kNN) for classification
- Brief mathematical background on SVM/li>
- Regression with kNN & SVM
Unsupervised learning in Python
- Need for dimensionality reduction
- Principal Component Analysis (PCA)
- Difference between PCAs and Latent Factors
- Factor Analysis
- Hierarchical, K-means & DBSCAN Clustering
Text Mining in Python
- Gathering text data using web scraping with urllib
- Processing raw web data with BeautifulSoup
- Interacting with Google search using urllib with custom user agent
- Collecting twitter data with Twitter API
- Naive Bayes Algorithm
- Feature Engineering with text data
- Sentiment analysis
Version Control using Git and Interactive Data Products
- Need and Importance of Version Control
- Setting up git and GitHub accounts on a local machine
- Creating and uploading GitHub Repos
- Push and pull requests with GitHub App
- Merging and forking projects
- Introduction to Bokeh charts and plotting
- Examples of static and interactive data products
We have made a tailored curriculum covering the latest industry-ready concepts to serve every individual’s learning desires.
Project Details
We bring you the best learning experience by delivering all our training sessions practical. Following are the few use cases we shall discuss during the training.
Machine Learning Training Objectives
1. What are the Machine Learning training course objectives?
By the end of Machine Learning training, you will be able to:
- Understand what machine learning is with the help of real-time examples.
- Master the concepts of supervised, unsupervised and reinforcement learning.
- Gain practical knowledge of principles, algorithms, and applications of machine learning.
- Acquire knowledge of the mathematical and heuristic aspects of machine learning.
- Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes.
- Model a wide variety of robust machine learning algorithms including deep learning.
2. Why should you learn the Machine Learning course?
- According to a recent survey, it is estimated that 64% of enterprises are investing in machine learning, creating huge job opportunities around the globe.
- Machine learning jobs are in high demand and top MNCs are hiring certified machine learning professionals worldwide.
- The average salary of a certified machine learning professional is around $103.875 USD per annum.
3. Who should attend Machine Learning training?
- Data Analysts
- AI and IoT developers
- Programmers
- Aspirants willing to build their career in the prospective field.
4. What are the prerequisites for learning Machine Learning training?
The following are the prerequisites for learning Machine Learning course:
- Understanding of data science
- Passion for new technologies
The following job roles will get benefited by taking up this course:
- Professionals in analytics
- Data scientists
- E-commerce site developers
5. What projects are included in this Machine Learning training course?
The tutor will take care of handling the projects. We will provide two real-time projects with a highly-skilled guide who can assist you throughout the project.
contact us
+1 930 200 4823
( Toll Free )
Training Options
Different individuals. Different upgrade goals. Different modes of learning.
We got solutions for everyone looking for an AWS Architect course. Opt in for your convenient upgrade option, and we will guide you through.
| Duration |
| One-on-one Session |
| Support |
| Resources |
| Time |
| Fee |
Live Online. |
| 25 Hours |
| Yes |
| 24x7 |
| Additional tips from the trainer |
30 July 2024, 07:00 AM 03 August 2024, 08:00 AM |
Self-Paced |
| 25 Hours |
| No |
| Weekdays & Working Hours |
| Accessible through LMS |
| At your convenience |
Machine Learning Training Upcoming Batches
Weekday
30 July 2024 to 30 August 2024
07:00 AM
Weekend
03 August 2024 to 03 September 2024
08:00 AM
Weekday
06 August 2024 to 06 September 2024
07:00 AM
Weekend
10 August 2024 to 10 September 2024
07:30 AM
Schedules Doesn't Suit You ?
Our Team can set up a batch at your convinient time.
Corporates Training
Experience and witness the express transformation of your workforce from the world-class tech upgrade platform.
Customized training options
Tailored curriculum to fit your project needs.
Practical exposure is assured.
We have got everything covered for any IT upgrade for your organization. We are one click away.
Success Stories from Future Digital Leaders
Machine learning classes taught by the Tekslate trainers are excellent. They guided me very well in the project. They have shown me the right path to get into the software industry.
Sony
I have recently enrolled for a machine learning training in Tekslate and have opted for weekend batch, they have options like weekday and weekend batches so you can do it in your free time. Their training has been really beneficial for me so far.
Virat
It is amazing to have the ML class from Tekslate...This is the first time I went through the online training mode and I have gained the confidence that I can continue my career ahead in the same domain.
Kareem
Machine Learning Training FAQ'S
Have questions? We’ve got the answers. Get the details on how you can grow in this course.
1. Who are the trainers?
We have a strong team of professions who are experts in their fields. Our trainers are highly supportive and render a friendly working environment to the students positively stimulating their growth.
2. What if I miss a class?
We will share you the missed session from our recordings. We at Tekslate maintains a recorded copy of each live course you undergo.
3. How will I execute the practical?
Our Trainers will provide the student with the Server Access ensuring practical real-time experience and training with all the utilities required for the in-depth understanding of the course.
Join a Free Machine Learning Training Demo Session
See if this course is a fit for you by joining us for an online info session. You’ll meet our team, get an overview of the curriculum and course objectives, and learn about the benefits of being a student at Tekslate