Խնդրում ենք Ձեր դիտարկիչի կարգավորումներից միացնել JavaScript-ը, էջի անխափան աշխատանքի համար։ Machine Learning Courses

Instructor

Seyed Ardalan
Hosseini

Python Developer,
Machine Learning Specialist
/ Develandoo /

Duration: 3 months

   |   

Price for a phase: 45.000 AMD

Machine Learning
(Artificial Intelligence)

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Taking into account the fact that there is a tendency of digital technologies’ development AI appears in such u huge companies as “Apple”, “Google”, “Microsoft”, “Intel” and many other famous companies. Thanks to Machine Learning you can turn your impossible ideas into reality.

Data Manipulation and Visualization
1st phase

1.Environment Set-up and Python (Crash course)
2.Numpy: Arrays, Indexing, Operations
3.Pandas: Series, IO, Manipulation
4.Pandas: Dataframes, Indexing, Columns
5.Pandas: Sorting, Null, apply method
6.Pandas: Groupby, Merging, MultiIndex
7.Retrieving, Processing, Storing Data
8.Matplotlib: Figures, Axes, Styles
9.Seaborn: Categorical, Regression, Grid
10.Plotly, Cufflinks and Pandas plot
11.Geographical plotting, Choropleth
12.Kaggle and Course Project
13.Test

Machine Learning (Theory and Practice)
2nd phase

1.Statistical Learning, Prediction Accuracy vs. Interpretability, Bias-Variance Tradeoff
2.Linear Regression, Qualitative Predictors
3.Classification, Logistic Regression, Linear Discriminant Analysis
4.K Nearest Neighbors, Comparisons of Methods, ROC curves, Confusion Matrix
5.Resampling Methods, Cross-Validation
6.Regularization, Subset Selection, Shrinkage, Dimension Reduction
7.Beyond Linearity, Polynomial Regression, Splines, Generalized Additive Models
8.Tree-Based Methods, Decision Trees, Bagging, Random Forests, Boosting
9.Support Vector Machines, Maximal Margin, Multi Classes
10.Unsupervised Learning, Principal Components Analysis, K-Means Clustering
11.Recommender Systems, Pearson correlation coefficient
12.Natural Language Processing, Count Vectorization, Pipeline
13.Project

Deep Learning
3rd phase

1.Neural Network, Deep representation, Binary Classification
2.Gradient Descent, Computation Graph ,Vectorization
3.Activation Functions, Forward/ Back propagation
4.Regularization, Vanishing/exploding Gradients, Mini-batch
5.Adam optimization, LR decay, Hyperparameters, Softmax
6.Orthogonalization, Test/Train/Dev sets, Avoidable Bias
7.Data Mismatch, Transfer/Multi-task Learning, End-to-End
8.CNN, Computer Vision, Edge Detection, Padding
9.ResNets, Inception, Face recognition, Siamese
10.Triplet Loss, Neural Style Transfer, Cost Function
11.RNN, Language Models, LSTM, Bidirectional RNN
12.NEmbedding Matrix, Word2vec, Beam search, Bleu Score
13.Project

Before starting to participate in programming courses there is a logical test intended to check mathematical reasoning and logical thinking

If you know one of the above-mentioned levels, you can simply pass to the next phase.

Every phase consists of 12 lessons, 3 lessons per week with the duration of 2 hours.

After each level there is a summary test, and if you get high points there will be up to 20% discount for the next phase.

During our trainings there is a motivational part that is practice.

After the completion of the whole course certificate is given.

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