Machine Learning training

Machine Learning Training

In the machine learning Training Course in Laxmi Nagar, we study such type of machine which takes the raw data from their environment and learn from these data and apply this information in future need. Machine learning is a part of Artificial Intelligence training that uses delay life data to learn themselves. Machine learning uses the techniques of pattern recognition. The machine observes the thing in a patterned manner and tries to understand these patterns according to its learning techniques.


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In this machine learning training, you will learn and collect the knowledge without using any kind of algorithms. In the early days, machine learning is a very good field for a career opportunity. nowadays many organization works on machine learning programs and hire the employees for it. For machine learning and artificial intelligence, the most used languages are the “R” language and python. Machine learning also used the concept of IoT Internet of Things.

Learn From Home with Online TrainingBytecode Cyber Security Provide 24x7 Classes

Students can attend classes from their homes. It takes less time to attend an online class. At the same time, various groups can attend online classes with bytecode Cyber Security From home.

Machine Learning Courses

Module 01: Introduction to Machine Learning
Module 02: Linear Regression
Module 03: Multiple Linear Regression
Module 04: Gradient Descent
Module 05: Saving Model to a File
Module 06: Dummy Variables & One-Hot Encoding
Module 07: Train-Test-Split
Module 08: Logistic Regression
Module 09: Multiple Logistic Regression
Module 10: Decision Tree
Module 11:  Random Forest
Module 12: K-fold Cross-Validation
Module 13: SVM
Module 14: K-Means Clustering
Module 15: Naive Bias
Module 16: One-Hot Encoding

Course Duration

  • Course Duration: 60 Hours
  • Course Level: Intermediate
  • Include: Training Certificate

Why Choose Machine Learning Training Course

Machine Learning Course is stretched and penetrated in the daily routine of us that even we don’t notice, the career in machine learning have the high and better opportunity as the world needs it and is getting higher in demand because the human being is getting dependent on the machines as technologies growing day per day, and that’s the reason why students who are just worrying about their career and have any interest in Artificial Intelligence going for machine learning course as it increases their package as well as get their market value higher. Bytecode Cyber Security provides this course training and certifications as affordable and cheap as compare to other institutes domestically or globally.

What is a NEW in Machine Learning Course?

  • Dummy Variables & One-Hot Encoding.
  • Know which Machine Learning model to choose for each type of problem.
  • Linear regression predicts a real-valued output based on an input value.
  • How Multiple Linear Regression work.
  • Basic Neural Networks & Deep Learning Algorithms

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About Machine learning training course program

Machine learning is all about making computers perform intelligent tasks without explicitly coding them to do so. This is achieved by training the computer with lots of data. Machine learning can detect whether mail is spam, recognize handwritten digits, detect fraud in transactions, and more.

machine-learning remains a relatively 'hard' problem. There is no doubt the science of advancing machine learning algorithms through research is difficult. It requires creativity, experimentation, and tenacity. The difficulty is that machine learning is a fundamentally hard debugging problem.

we have covered some of the most important machine learning algorithms for data science: 5 supervised learning techniques- Linear Regression, Logistic Regression, CART, Naïve Bayes, KNN. 3 unsupervised learning techniques- Apriori, K-means, PCA

On one hand, data science focuses on data visualization and a better presentation, whereas machine learning focuses more on the learning algorithms and learning from real-time data and experience

  1. Naïve Bayes Classifier Algorithm
  2. K Means Clustering Algorithm
  3. Support Vector Machine Algorithm
  4. Apriori Algorithm
  5. Linear Regression Algorithm
  6. Logistic Regression Algorithm