Machine Learning Training
About Machine Learning
Today’s world is advancing with technology. If we observe from the past decade Artificial Intelligence, and Machine Learning are emerging into the computer science world taking the technology to the next level. Machine Learning is simply nothing but the computers to act themselves without a definite program. our Lucency Technologies is the best institute for machineachine learning training in KPHB Hyderabad.we are providing Internships on Machine Learning and Artificial Intelligence also.For the purpose of Data Analysis, Machine Learning is extensively used as the high-level application platform. Many of us think that Machine Learning is almost similar to Artificial Intelligence but it is totally misconception, using Machine Learning we can do Data Mining. In order to automate the decision models, Machine Learning is exclusively implemented. Today’s world is advancing with technology. If we observe from the past decade Artificial Intelligence, and Machine Learning are emerging into the computer science world taking the technology to the next level. Machine Learning is simply nothing but the computers to act themselves without a definite program. For the purpose of Data Analysis, Machine Learning is extensively used as the high-level application platform. Many of us think that Machine Learning is almost similar to Artificial Intelligence but it is totally misconception, Machine Learning is similar to that of Data Mining. In order to automate the decision models, Machine Learning is exclusively implemented.
Lucency Technologies is having expert staff in training Machine Learning with Python. Our working professionals are well versed with the techniques in training Machine Learning with Python. Machine Learning with Python has some special value because it is having a strong hold in creating ML algorithms. This combination is universally accepted as the best and robust platform for having machine learning systems. The reason why Python is popular with Machine Learning is because the Python is having some special libraries for performing algorithms in machine learning.Prerequisites:
- Dedication and interest to learn the subject.
- Basic programming skills and knowledge on OOP’s concepts.
- Basic knowledge on Mathematics and Statistics.
Machine Learning Basics
- You will have the introduction to the data and data analysis how the Data Science and Artificial Intelligence are evolving and used in the highly reputed organizations. Introduction to Machine Learning
- You will have an introduction to what is Machine Learning and how machines learn.What are the types of learning and basics of algorithms. You will also learn to choose Machine Learning algorithm. Taking Back to basic Math’s and Statistics
- In this session you will have a quick refresh on the basics of Math’s and Linear Algebra. Your Probability and Statistic basics will also be refreshed. Time to start Python
- You will learn the basics of Python, Data handling, concepts of loops, conditions and functions and how these works with Machine Learning. Data Processing in Machine Learning
- You will learn Data collection and Preparation of data. Concepts of Feature Engineering and Data Transformation are explained. Differentiating Normalization vs Standardization. How to create dummies and principle component analysis. Advanced Algorithm in Machine Learning
- In this you will learn the concepts of different types of learning’s and algorithms in advanced way. Clustering with K-Means clustering, regularization and grid search optimization. Doing Projects
- Implementing the concepts learned above in a project with real life cases. Our efficient staff will guide you and help you while doing the project.
Structure of our Machine Learning Syllabus Follows.
MACHINE LEARNING SYLLABUS
NOTE: Almost every task is explained with an exampleIntroduction along with Q&A Section:
- What is machine learning?
- What is Data Science?
- What is Artificial Intelligence?
- What are the Programming Languages and how much Proficiency required being successful in this stream?
- How Much Mathematics is required for ML, Data science, Artificial intelligence?
- What are the different tools, Techniques and libraries we are going to Use in this course curriculum?
- How much Practical Exposure you will get in this course?
- How Much Time you need to spend in day for this course?
- What is The Course Duration? Months /Days
- How will be the course structure, and Learning Methodology?
- What are the Roles and Responsibilities/ Designations in the Industry for these Areas?
- What are the Prerequisites to choose, this as a carrier Opportunity?
- It is your requirement / for a better carrier you choose this or Passion? Or Technology Upgrading Process. Commitment or desire to learn.
- You need to clarify you are eligible for this course or not?
Some decent Level of common-sense.
Tenth class level Mathematical Understanding and willing to learn Mathematics.
Willing to Adoptable Logical and Reasoning based Thinking Style.
Even you have zero Programming skills, willing to learn and Practice
- Reading and Interpreting the data
- Ratios, Rates, Proportion’s
- Equations, Expressions, Inequalities
- Exponents, Radicals Scientific Notations
- Algebraic Expressions
- Graphing Lines and Slope
- Quadratics and Polynomial’s
- System of Equations
- Equations and Geometry
- Complex numbers
- Exponential Growth and Decay
- Exponentials and Logarithm’s
- Vectors and Spaces
- Matrix transformations
- Alternate Coordinate systems
- Introduction to Statistics
- Descriptive Statistics
- Random Variables
- Normal Distribution
- Sampling and Sampling Distributions
- Confidence Intervals
- Hypothesis Testing
- The comparison of two populations
- Analysis of Variance (ANOVA)
- Simple Linear regression and Correlation
- Multiple Linear Regression
- Forecasting, Time Series
- Bayesian Statistics and Decision Analysis
- Sampling Methods
- Multivariate Analysis
- Using Python As a calculator
- Value Assignment
- Data Types in Python
- Simple Arithmetic Operations
- Comparison Operators
- Type Functionality
- Data type Conversions