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Data Science 2020 Data Science & Machine Learning in Python

Data Science 2020: Data Science & Machine Learning in Python

Hands-On Data Science, Machine Learning, Deep Learning, TensorFlow 2.0, Python for Data Science, Data Analysis, More !

According to an IBM report, Data Science jobs would likely grow by 30 percent. The estimated figure of job listing is 2,720,000 for Data Science in 2020. And according to the US Bureau of Labor Statistics, about 11 million jobs will be created by 2026. Data Science, Machine Learning and Artificial Intelligence are hottest and trending technologies across the globe, almost every multinational organization is working on it and they need a huge number people who can work on these technologies. By keeping all the industry requirements in mind we have designed this course, with this single course you can start your journey in the field of Data Science

Best Seller CourseCOVID-19 Data Science Urban Epidemic Modelling in Python

What you’ll learn

  • Go from total beginners to confident machine learning engineer
  • Apply Machine Learning algorithm on 10+ dataset
  • Get complete Environment ready with Google Colab Notebook
  • Machine Learning Overview, Types of Machine Learning System
  • Compare Machine Learning with Traditional system of Computing
  • Different Machine Learning Algorithm, Machine Learning Workflow
  • Transform your data with One Hot Encoding & Feature scaling
  • Apply Natural Language Processing Technique like Tokenization, Stemming, Stop Words, Named Entity Recognition, Sentence Segmentation
  • Classify Fashion clothes image with Artificial Neural Network + Keras
  • Importing Libraries, Importing Dataset, Working with missing data
  • Build Credit Card Fraud Detection with Convolution Neural Network
  • Theory behind Convolutional Neural Networks, Different layers in Convolutional Neural Networks
  • The Neuron, Activation Function, Cost Function, Gradient Descen
  • Theory behind Recurrent Neural Networks, Vanishing Gradient Problem
  • Classify IMDB Review using Recurrent Neural Network – LSTM
  • Pandas Series, DataFrames, Multi-index and index hierarchy
  • Working with Missing Data, Groupby Function, Merging Joining and Concatenating DataFrames
  • Pandas Operations, Reading and Writing Files
  • Predict Restaurant Profit with Multiple Linear Regression
  • Calculate Grades using Simple Linear Regression
  • Apply SVR, SVM, Decision tree and Random Forest on Real Dataset
  • Get Hands-on with Python Crash Course
  • Refresh concept of Data analysis and Visualization with NumPy, Pandas & Matplotlib
  • Plots different types of Chart like Scatter Plot, Bar plot, Histogram, Pie Chart

You May Also Need This CourseComplete Machine Learning and Data Science: Zero to Mastery

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