Machine Learning (ML) is a sub-field of artificial intelligence. It concerns giving computers the ability to learn without being explicitly programmed. Over the years, machine learning’s popularity and demand has certainly been on the rise.According to Indeed, the average salary for a machine learning engineer in the United States is $134,655. But what is so special about it that it’s one of the highest paid jobs in programming?

Interested ? This course “Machine Learning With Python Programming” has been designed to help you learn complex theory, algorithms and coding libraries in a simple way.

you will be taught concepts like Data Preprocessing , Regression , Classification , Clustering , Reinforcement Learning , Natural Language Processing , Machine Learning on Big Data using Apache Spark and Deep Learning .

The course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.

Syllabus and Projects

[expand title=”Getting Started”]

• Introduction To Machine Learning
• Machine Learning Definition
• Need for machine learning
• Machine Learning Techniques
• Applications Of Machine Learning
• Machine Learning Vs Deep Learning Vs Artificial Intelligence

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[expand title=”Programming with Python(Hands-On) “]

• Python Basics
• Introduction to Jupyter Notebook
• Pandas
• Numpy
• Scikit-learn

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[expand title=”Statistics and Probability”]

• Descriptive Statistics
• Skewness and kurtosis
• Inferential Statistics (Hypothesis Testing)
• Types Of Data
• Types Of Data Distribution
• Correlation and Causation
• Central Limit theorem
• Bayes Theorem
• Conditional Probability
• Application of statistics in real time data with hands-on

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[expand title=”DATA WRANGLING AND VISUALIZATION”]

• Problem and Data Understanding
• Typecasting
• Missing Value Imputation
• Outlier Detection and Treatment
• Handling Duplicates
• Normalizing values
• String Manipulation
• Visualization with matplotlib and seaborn

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[expand title=”FEATURE ENGINEERING”]

• What is feature engineering?
• Transforming Nominal Features
• Transforming Ordinal Features
• Feature Scaling
• Standardized Scaling
• Min-Max Scaling
• Feature Selection
• Threshold based selection
• Recursive Feature Elimination
• Model-Based Selection
• Dimensionality Reduction
• Principal Component Analysis
• Linear Discriminant Analysis

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[expand title=”SUPERVISED MACHINE LEARNING “]

• What is supervised machine learning
• Types of Supervised Machine learning
• What is regression problems
• Assumptions of Linear Regression
• Simple Linear Regression
• Multiple Linear Regression
• Evaluation Metrics of Regression Problems
• What is classification problems
• Classification Algorithms
• Assumptions of Logistic Regression
• Logistic Regression
• Evaluation Metrics of Classification Problems
• Decision Tree Classifier
• Ensembling Methods
• Random Forest Classifier
• Gradient Boosting
• XGBOOST
• Naive Bayes
• K – Nearest Neighbors (KNN)
• Support Vector Machine (SVM)

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[expand title=”UNSUPERVISED MACHINE LEARNING “]

• Clustering
• K -means Clustering
• Hierarchical Clustering
• Elbow Method

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[expand title=”RECOMMENDATION SYSTEM “]

• Application Of Recommendation system
• Collaborative Recommender System
• Content Based Recommender System
• Association rule mining
• Apriori Algorithm
• Market Basket Analysis

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[expand title=”MACHINE LEARNING MODEL BUILDING “]

• Splitting data into Train data and Test data
• Machine Learning Framework
• Model Selection
• Hyperparameter Tuning
• Model Evaluation (Evaluation Metrics)
• K- Fold Cross Validation
• Overfitting and Underfitting
• Hands-on Project : Fraud Detection using Credit data

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[expand title=”Reinforcement Learning “]

• Introduction to Reinforcement learning
• Terminology
• Environments
• How Reinforcement Learning Works
• ϵ (epsilon)-greedy algorithm
• Markov Decision Processes

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[expand title=”TIME SERIES FORECASTING “]

• Time series components
• Smoothing Techniques
• Auto Regression
• Moving Average
• Autoregressive Integrated Moving Average (ARIMA)
• Hands-on Project : Stock Price Prediction

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[expand title=”UNSTRUCTURED DATA ANALYSIS”]

• What is Unstructured Data Analysis
• Types of Unstructured Data
• Introduction to Natural Language Processing (NLP)
• Text Data Preprocessing(tokenization,stemming,lemmatization)
• hands -on Project ​:​ Topic modelling using ​Latent Dirichlet allocation algorithm

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[expand title=”Deep Learning”]

• Introduction to Deep Learning
• Artificial Neural Network(ANN) and Convolutional Neural Network(CNN)
• Introduction to Image Processing
• Image data Preprocessing
• Hands- on Project : Image Recognition with CNN algorithm Using Keras

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[expand title=”Final Project”]

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• Regular classes – 4 weeks
• Weekend Classes – 6 weeks
• Customized Fast Track option is available as well. Call +91-80-306-306-47 now to customize according to your requirement

• Experienced IT professionals
• Having hands on practical knowledge
• With experience of training large batches in both offline and online mode

• Online Self Paced Training (SPT) with Videos and Documents
• Online Instructor Led Training (ILT)

About the course:

Study9 provides a robust job market focused Machine learning  training. Our Machine learning  course is designed with the right mix of basic and advanced topics to get one started in the domain and enable a person to get a good job in this competitive market. Our Machine learning  trainers are experienced professionals with hands on knowledge of Machine learning  projects. The Machine learning  course content is designed with keeping the current job market’s demands in mind.Our Machine learning  training course is value for money and tailor made for our students.

About Study9 Training Method

Study9 provides a robust job market focused Machine learning training. Our Machine learning course is designed with the right mix of basic and advanced topics to get one started in the domain and enable a person to get a good job in this competitive market. Our Machine learning trainers are experienced professionals with hands on knowledge of Machine learning projects. The Machine learning course content is designed with keeping the current job market’s demands in mind.Our Machine learning training course is value for money and tailor made for our students.